Research ArticleStudy on Electric-Magnetic-Acoustic Signal Regularity and ItsCorrelation during Rock Shear Failure

Huilin Jia 12 Yue Niu 13 Xiaofei Liu13 and Enyuan Wang13

1State Key Laboratory of Coal Resources and Safe Mining China University of Mining and Technology XuzhouJiangsu 221116 China2Department of Vocational and Continuing Education China University of Mining and Technology XuzhouJiangsu 221116 China3School of Safety Engineering China University of Mining and Technology Xuzhou Jiangsu 221116 China

Correspondence should be addressed to Huilin Jia hljcumteducn and Yue Niu name_niuyue163com

Received 8 May 2019 Revised 29 June 2019 Accepted 8 July 2019 Published 18 July 2019

Guest Editor Grzegorz Lesiuk

Copyright copy 2019 Huilin Jia et al is is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

During mining activities the deformation and damage of coal rock materials might result in coal rock dynamic disasters such asrock burst It leads to serious casualties and property losses Generally the occurrence of dynamic failure of coal and rock arecaused by shear failure of coal seam Geophysics signals are generated and related to damage evolution in this loading process Inthis paper sandstone samples were subjected to shear failure laboratory experiments and the electric-magnetic-acoustic signalregularity was measured and analyzed comparatively e results indicated magnetic signals were more correlated with stress andacoustic emission (AE) signals while the amplitude of electric signal fluctuation was larger when main failure occurred With theincrease of sample size and shear strength the strength of electric-magnetic-acoustic signals increasede correlation coefficientsbetween the magnetic signal and stress as well as AE energy were superior to those of electric signalse coupling model betweenAE and electric signals was established which shows good statistical correlation is study lays the foundations for furtherinterpreting the generation mechanism of the electric signal It provides a new method to indicate the damage evolution of coalrock materials

1 Introduction

Generally coal resources play a significant role during theenergy consumption especially for industrial raw materialsand electric power production [1ndash3] Nevertheless coal rockdynamic failure and even disasters occur during miningactivities which results in serious casualties and propertylosses [4ndash7] Coal or rock fracture roof collapse and faultactivation in mines are all accompanied by shear failurewhich will further induce mine earthquake rock burst coaland gas outburst and other dynamic disasters [2 8] It is ofgreat significance to determine damage sources and theircharacteristics for predicting dynamic disasters in coalmines [9ndash11]

During the damage and failure process of the rockacoustic emission (AE) signals are generated [12] ereforeAE technology is used to study the expansion and evolution

mechanism of cracks [13 14] Khazaei et al analyzed thevariations in b values energy of acoustic emission for rockspecimens during 73 uniaxial compression tests [15] Lianget al investigated the mechanical and acoustic emissioncharacteristics of the rock during loading and unloadingconfining pressures at the postpeak stage [16] Wang et alinvestigated the features of similar material mechanics andconcluded that the law of AE behavior and the character-istics of similar material fracture can obtained the regularityof stress and deformation during material loading processes[17] Kong et al concentrated on the thermal mechanicalproperties and AE characteristics during the deformationand fracture of the rock under the action of continuousheating and after high-temperature treatment [18]

In addition to AE signals electromagnetic radiation(EMR) has been recognized and analyzed in rock failure andearthquake precursor observation in early days [19ndash21]

HindawiAdvances in Materials Science and EngineeringVolume 2019 Article ID 4687607 12 pageshttpsdoiorg10115520194687607

Freund and Sornette revealed the mechanism for the low-frequency electromagnetic emissions and electric phe-nomena and conjectured the intermittent and erratic oc-currences of EMR signals are a consequence of theprogressive and of their release which provided a con-ductive pathway [22] Gade et al argued that the electro-magnetic signals are generated as a result of the collaborativeconsequence of charge separation relaxation and vibrationof charged crack surface during the growth of cracks [23]Interestingly Carpinteri et al reported that growth of bothmicrocracks and macrocracks would lead to EMR signals[24] Wang et al reported that coal rock materials couldproduce ultralow frequency (ULF) EMR signals during thedamage and failure processes and the change trend of thesignals was well similar to stress and AE signals [25] Topredict the collapses more accurately using EMR a loadedcoal rock EME coupling model based on statistical damagemechanics was established [26] Kong et al studied the time-varying characteristics of EMR during three metamorphicgrades of the coal-heating process [27]

Owing to the complexity of rock outburst the precursorsignals of AE and EMR might be not very obvious but withimprovements in monitoring methods the electric signals arebeginning to be analyzed gradually [11 28ndash30] Freund hastried to establish the physically coherent model for resistivitychanges ground potentials and electromagnetic behavior andexplained the mechanism of earthquake-related electricalsignals and emission [31] Li et al studied the surface potentialof coal during different fracture modes including uniaxialcompression tensile fracture and three-point bending andconcluded that surface potential was produced during thefracture of coal and that it had a good correspondence to theload [32] To explain the mechanism of electric potential (EP)the change law and distribution characteristics of electricpotential were tested with the precracked rock samples andfree charges were found to be produced at the tip of the cracksand the newly formed crack surface [33]

Several studies on AE EMR and electric signals havebeen published However studies evaluating these signals inshear failure especially rock shear failure are scarce Be-sides the correlation characteristics of electric-magnetic-acoustic signal regularity were not reported In this paperunder shear failure the electric-magnetic-acoustic signalregularity of sandstone was studied and the impact ofsample size on experimental results was analyzed Fur-thermore the correlation characteristics among electricsignals EMR AE and stress were illustrated Variation lawsof the electric signal were interpreted by establishing anacoustic-electric coupling model It is promising to furtherreveal the dynamic disaster process of coal rock materialsand perfect the EMR theory as well as the corresponding testequipment

2 Materials and Experimental Procedure

21 Material Preparation e tested rock samples werecollected from roof sandstones of Sanhejian Coal Mine inXuzhou China According to the International Society forRock Mechanics (ISRM) standard samples were prepared

and processed in Strata Control Experimental Center StateKey Laboratory of Coal Resources and Safety Mining ofChina University of Mining and Technology After samplecoring two types of specimen (50mmtimes 50mmtimes 100mmand 50mmtimes 50mmtimes 50mm) were prepared e preparedstandard specimen was labeled and kept in a glass containerthat was sealed up with Vaseline to preserve the original stateof the specimen

22 Test System e experimental system mainly includeshydraulic loading devices data-acquisition system varioussensors etc (Figure 1) Loading system the control systemis an electrohydraulic servo pressure-testing machine(YAW4306) and the maximum pressure is 3000 kN eloading process can fully realize program control and cansimultaneously collect parameters such as stress and dis-placement during the whole loading process at high speede LB-IV electric signal data-acquisition system was usedto collect the low-frequency electric signal during de-formation and failure process of the rock Data samplingfrequency could be set arbitrarily below 1000Hz efrequency of sensors used to collect the low-frequency andacoustic andmagnetic signals is higher than that of the low-frequency electric signal so the CTA-1 acoustic-electricdynamic high-speed data-acquisition system manufac-tured by Physical Acoustics (American) was used

Signal sensors the copper electrodes (Figure 2(a)) wereused to receive low-frequency (lt1 kHz) electric signals AEsensors (Figure 2(b)) with 423 kHz resonant frequency wereused to monitor acoustic signals and the ferrite rod an-tennas (Figure 2(c)) of low frequency (1 kHz and 5 kHz) andcommon frequency (300 kHz) were used to collect magneticsignals In the experiments the cooper electrodes and theacoustic emission sensors were fixed onto the rock samplesurface using adhesive tapes A Vaseline coupling agent wasused at the contact surface to ensure the elastic wave isreceived by the sensors e ferrite rod antennas werearranged around the specimen less than 10 cm away fromthe specimen

23 Test Scheme Shear strength of the rock is the tangentialstress on the shear surface when rocks suffer shear failureand is the ultimate strength of the rock at shear failure eoblique compression molding method is widely used to testthe shear strength of the rock with which the normal stress(σ) and shear stress (τ) on the shear failure surface can becalculated

e laboratory rock shear experiment and the layout ofsensors are shown in Figure 3 Two electrodes were pasted onthe specimen surface about 10mm to two sides of the shearsurface AB respectively and the third electrode was pasted onthe upper left corner of the rear surface of the specimen10mm away from the specimen edge e AE sensor wasattached at the bottom left corner of the rear surface of thespecimen 5mm away from the specimen edge e preparedrock specimenwas placed in between two angle-variable shearclamps and shear force was applied onto the specimen bycontrolling the loading rate During the loading process the

2 Advances in Materials Science and Engineering

electric acoustic and magnetic signals were monitored si-multaneously Finally the sample would experience failurealong the preset shear surface of AB

3 Electric-Acoustic-Magnetic Signals uponRock Shear Failure

31 Sample 1 e stress law and electric-magnetic-acoustic signal regularity of sample 1 are presented inFigures 4(a)ndash4(h) e size of shear failure surface wasabout 50mm times 100mm From Figure 4(a) it can beconcluded that the maximum shear strength of sample 1was 468MPa Clearly stress AE and EMR changed al-most similarly throughout the whole loading process Inthe initial 30 s a self-balancing process of the shear moldoccurred Subsequently shear force increased graduallyAt 95 s the magnetic signals of channel 5 (ch5 Figure 4(f ))and those of channel 8 (ch8 Figure 4(h)) showed ananomalous response e signals increased rapidly anddecreased immediately Subsequently the AE signals(Figure 4(e)) presented obvious changes when stressfluctuates slightly after 107 s Compared with AE signalslow-frequency magnetic signals occurred earlier After120 s stress increased quickly and the magnetic signalsincreased accordingly At 160 s stress reached 434MPawhich is close to the peak intensity At this moment themain macrocrack is formed e stress fluctuates violentlywhereas AE and magnetic signals reach the peak values At176 s the shear surface was cut through and stress sud-denly dropped to 0 e corresponding channel signalsdeclined quickly

e electric signals of different channels differed sig-nificantly during the whole loading process e electricsignals are slightly weak in Channel 2 (ch2 Figure 4(b)) andChannel 9 (ch9 Figure 4(d)) because the sensors of twochannels did not contact with the rock surface directlyBefore the main failure the overall variation of electricsignals was only about 2mV in these channels whereas ahuge amplitude of variations was detected after the de-velopment of main fracture Considering the direct contactbetween electrode and the sample surface the electricsignals from channel 8 (ch8 Figure 4(c)) were more sen-sitive and produced violent increase and reduction whenstress fluctuated at 107 s which was consistent with thevariation trends of AE and EMR After 120 s the EMRsignal had the increase trend which is correlated with thecontinuous increase of stress Later pulse fluctuation

became increasingly frequent in the early stage of shearfailure until the occurrence of the main failure and thesignal variation amplitude of all channels reached the peakIn general the electric signal was slightly correlated withstress but was closely related to fluctuation of the AE signalHowever the electric signal fluctuates upon stress fluctu-ation or generation of the AE signal

32 Sample 2 Sample 2 was also collected from roofsandstone at the same position as Sample 1 but the size ofshear surface in the former was 50mmtimes 100mm Ac-cordingly the failure load was decreased to 67 kN but theyhad the same shear strength It could be concluded that thereis a good correlation between low-frequency magnetic signalof channel 5 (ch5 Figure 5(f)) channel 7 (ch7 Figure 5(g))and the stress However the magnetic signal of channel 8(ch8 Figure 5(h)) was relatively weaker showing no obviousvariation throughout the loading process During theloading process two internal damages were detected at 75 sand 123 s and the main failure occurred at 140 s e AEsignal had strong responses at these three time points and itwas stronger at 75 s than that at 123 s Interestingly as shownin Figure 4(f ) the EMR signal met its valley values around75 s 123 s and 140 s It is most striking around 123 sMeanwhile in Figure 4(h) the EMR signal met its significantmutation response around 123 s while the response is lessremarkable around 75 s and 140 s Compared with Sample 1the overall electric-magnetic signal strength was significantlyweaker In particular the high-frequency magnetic signalwas not only weak but also poorly corresponding to thestress and AE signal

e variation law of low-frequency electric signal wassimilar to that of Sample 1 e signals of channel 2 (ch2Figure 5(b)) and channel 9 (ch9 Figure 5(d)) changed onlyslightly about 1mV before the occurrence of main fractureBy contrast they changed significantly after the main failuredeveloped Because of the higher sensitivity the electricsignal of channel 8 (ch8 Figure 5(c)) fluctuated greatly whenstress began to change at 75 s and it presented the secondchange at 123 s when the overall basic value had reducedis implied that the internal failure at 75 s brings aboutsome negative charges surrounding the 8 test point Be-cause of the weak electroconductivity of the rock this po-tential remained constant until the abundant new chargesformed at the second fracture site (123 s) When the mainfailure occurred at 140 s the amplitude of signal fluctuationof channel 8 reached the maximum but this was still smallerthan that of Sample 1 is indicated that sample size couldaffect intensity of the electric signal but they had consistentvariation tendency

4 Discussion

41 Electric-Magnetic Signal Generation Mechanism evariable motion of charges is an important way to generatethe electric-magnetic wave and includes two mechanismssuch as vibration or transition of electric dipole and re-laxation of separated charges Most mechanisms of EMR

Figure 1 Experimental system

Advances in Materials Science and Engineering 3

generation induced by deformation and failure of coal orrock are related to development of cracks One is asymmetriccharges along the axial direction of cracks for exampleelectric dipole model e other is positive and negativecharges generated on cracks wall such as variable motion ofcharges and relaxation of separated charges caused byfriction electrification or piezoelectric effect erefore it isnecessary to study how charges are generated and movedwhen exploring the mechanism of EMR generation uponstress failure of coal or rock

In these experiments the rock suffered shear failurewhich is different from tensional failure erefore there isresidual stress on crack surfaces even after sufficient slidingof these surfaces Such residual frictional resistance could beregarded as the main source of stress Meanwhile the energyrelease rate of shear failure was two magnitudes higher than

that of tensional failure In other words shear failure re-leased an increased concentration of energy at the failurewhich was related to different development processes ofshear cracks and tensional cracks at the end point

In the shearing process charges of different polaritieswould be generated on the upper and lower shear surfaceswhich were attributed to piezoelectric effect frictional effectand asymmetric breakages of crystal bonds (Figure 6)

Charge generation induced by the piezoelectric effect ismainly manifested during growth of cracks With the ex-tension of cracks the stress of microunit on the uppersurface of cracks changes significantly thus attractingcharges to some microunits containing piezoelectric mate-rials After further extension of the cracks these microunitsare distributed on the upper and lower surfaces of the cracksmaking both upper and lower surfaces charged When themain crack was cut through (ie the failure of materials)charges generated by the piezoelectric effect are reducedwhich would contribute less to EMR signals

EMR signal induced by triboelectric charge existsthroughout the whole shear failure However its contributionsare different in different stages During the early loading perioddue to the small pressure stress the relative displacementbetween upper and lower surfaces of the cracks was very smalland the electrification by friction was relatively weak Never-theless the relative displacement between upper and lowersurfaces increased significantly after the principal crack was cutthrough accompanied by strong friction effect and increasedgeneration of charges both of which contributed to increasedgeneration of EMR signals Meanwhile the contributions offriction effect to the EMR signal under shear failure changedwith the shear angle Obviously friction played a greater roleunder a small shear angle and high-pressure stress

ese effects influence the whole shear failure processtogether resulting in the continuous accumulation of chargeson the upper and lower crack surfaces Moreover rock ma-terials are of poor conductive features which have low rate ofcharge release Charges in rockmaterials will not disappear in ashort period but instead move with the surface displacementBecause the total charge on crack surface increases continu-ously the electric signal strengthens gradually in the wholefailure process when viewed from the macroscopic perspectiveBesides the distance between the testing point and chargeschanged when upper and lower surfaces had relative dis-placement thus causing the pulse fluctuation of the electricsignal is conforms to the variation law of the electric signal

(a) (b) (c)

Figure 2 Sensors (a) Electrode (b) AE sensor (c) Ferrite rod antenna

1ndash3 Electrodes4 AE sensor5 Ferrite rod antenna

5

34

2

1

5

a

B

A

Figure 3 Shearing equipment 1ndash3 electrodes 4 AE sensor 5 ferriterod antenna

4 Advances in Materials Science and Engineering

0

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ress

(MPa

)

Load value

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Electric-ch2

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ndash20000

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20000

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Ener

gy (m

J)

EMR (1kHz)-ch5

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(f )

Figure 4 Continued

Advances in Materials Science and Engineering 5

observed in the experiments Furthermore the motion ofcharges generates the EMR signal

42 Correlation of Various Signals At present most scholarsaccept that sample damages and failures could be analyzed byvariation of stress and AE signal If the high correlationbetween electric-magnetic signals and stress as well as AEcould be proved it would lay foundations for using electric-magnetic signals to analyze sample damage and dynamicdisasters of coal or rock Based on the aforementionedanalysis we found that there is certain correlation betweenelectric-magnetic signals and stress as well as AE Meanwhilethe correlation between EMR signal of conventional fre-quency and AE as well as stress has been recognized by mostscholars However no quantitative evaluation index wasproposed for such correlation In this paper the correlationcoefficient (|r|) between electric-magnetic signals and stressas well as AE was calculated using the Origin mathematicalsoftware which was used to evaluate their consistency

Take the correlation between stress and electric signal(Figure 7(a)) for example It demonstrated low linear cor-relation between two signals when the calculated maximumcorrelation coefficient |r|lt 04 significant correlation when04le |r|lt 07 and high linear correlation when 07le |r|lt 1When the delay (τ) corresponding to the maximum cor-relation coefficient is negative stress changes earlier than theelectric signal otherwise the electric signal changes earlier

e calculated correlation coefficient between electric-magnetic signals of Sample 1 and stress as well as AE isshown in Figure 7 In most cases τ is close to 0 but in somecases τ is not 0 Corresponding to the maximum correlationcoefficient between stress and electric signal of channel 8(Figure 7(a)) τ was 10 s indicating that electric signalchanged earlier than stress However the electric signal dataof channel 9 lagged for 2 s behind the stress (Figure 7(a)) In

Figure 7(d) the delay between the magnetic signal ofchannel 5 and channel 8 and AE signal of channel 2 was 2 sindicating that the EMR signal changed earlier than the AEsignal Besides correlation coefficients of electric signal hadpositive and negative values which were related to accu-mulation of positive and negative charges in the electroderegion A similar phenomenon was observed in correlationcoefficients of Sample 2 (Table 1) Meanwhile we calculatedanother experimental data other than those used in thispaper According to various estimates the correlation co-efficient between electric signal and stress might be eitherpositive or negative at equivalent probability is was alsocaused by different charge polarities of different regionsupon deformation or failure of the rockWhenmore positivecharges accumulate in one region the local electric signalincreased generally forming a positive correlation withstress variation Otherwise more negative charges accu-mulate resulting in the negative correlation between theelectric signal and stress

Table 1 presents peak correlation coefficients of signalsfrom Samples 1 and 2 Based on a comparison of 12 groupscorrelation coefficients between electric-magnetic signalsand stress were higher than those between electric-magneticsignals and AE in eight groups correlation coefficients wereclose to those between electric-magnetic signals and AE intwo groups and correlation coefficients were smaller in twogroups With respect to correlation coefficients betweenstress and electric-magnetic signals there were high linearcorrelation (in 6 groups) significant correlation (in 3groups) and low linear correlation (in 3 groups) Howeverconcerning the correlation coefficients between AE andelectric-magnetic signals there were no high linear corre-lation significant correlation (in 9 groups) and low linearcorrelation (in 3 groups) erefore the correlation betweenmagnetic signal and stress as well as AE was superior to thatof the electric signal

ndash20 0 20 40 60 80 100 120 140 160 180 200

0

100

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400

500

600En

ergy

(mJ)

Time (s)

EMR (5kHz)-ch7

(g)

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140 160 180 200

800

1000

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1400

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1800

2000

Time (s)

EMR (300kHz)-ch8

(h)

Figure 4 Electric-magnetic-acoustic signals of 1 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

6 Advances in Materials Science and Engineering

0

10

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Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

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(a)

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tric

(mV

)

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(mV

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Ener

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Ener

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J)

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Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

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ergy

(mJ)

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Ener

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J)

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Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

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00

02

04

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08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

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00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

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0

10

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30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

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Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

electric acoustic and magnetic signals were monitored si-multaneously Finally the sample would experience failurealong the preset shear surface of AB

3 Electric-Acoustic-Magnetic Signals uponRock Shear Failure

31 Sample 1 e stress law and electric-magnetic-acoustic signal regularity of sample 1 are presented inFigures 4(a)ndash4(h) e size of shear failure surface wasabout 50mm times 100mm From Figure 4(a) it can beconcluded that the maximum shear strength of sample 1was 468MPa Clearly stress AE and EMR changed al-most similarly throughout the whole loading process Inthe initial 30 s a self-balancing process of the shear moldoccurred Subsequently shear force increased graduallyAt 95 s the magnetic signals of channel 5 (ch5 Figure 4(f ))and those of channel 8 (ch8 Figure 4(h)) showed ananomalous response e signals increased rapidly anddecreased immediately Subsequently the AE signals(Figure 4(e)) presented obvious changes when stressfluctuates slightly after 107 s Compared with AE signalslow-frequency magnetic signals occurred earlier After120 s stress increased quickly and the magnetic signalsincreased accordingly At 160 s stress reached 434MPawhich is close to the peak intensity At this moment themain macrocrack is formed e stress fluctuates violentlywhereas AE and magnetic signals reach the peak values At176 s the shear surface was cut through and stress sud-denly dropped to 0 e corresponding channel signalsdeclined quickly

e electric signals of different channels differed sig-nificantly during the whole loading process e electricsignals are slightly weak in Channel 2 (ch2 Figure 4(b)) andChannel 9 (ch9 Figure 4(d)) because the sensors of twochannels did not contact with the rock surface directlyBefore the main failure the overall variation of electricsignals was only about 2mV in these channels whereas ahuge amplitude of variations was detected after the de-velopment of main fracture Considering the direct contactbetween electrode and the sample surface the electricsignals from channel 8 (ch8 Figure 4(c)) were more sen-sitive and produced violent increase and reduction whenstress fluctuated at 107 s which was consistent with thevariation trends of AE and EMR After 120 s the EMRsignal had the increase trend which is correlated with thecontinuous increase of stress Later pulse fluctuation

became increasingly frequent in the early stage of shearfailure until the occurrence of the main failure and thesignal variation amplitude of all channels reached the peakIn general the electric signal was slightly correlated withstress but was closely related to fluctuation of the AE signalHowever the electric signal fluctuates upon stress fluctu-ation or generation of the AE signal

32 Sample 2 Sample 2 was also collected from roofsandstone at the same position as Sample 1 but the size ofshear surface in the former was 50mmtimes 100mm Ac-cordingly the failure load was decreased to 67 kN but theyhad the same shear strength It could be concluded that thereis a good correlation between low-frequency magnetic signalof channel 5 (ch5 Figure 5(f)) channel 7 (ch7 Figure 5(g))and the stress However the magnetic signal of channel 8(ch8 Figure 5(h)) was relatively weaker showing no obviousvariation throughout the loading process During theloading process two internal damages were detected at 75 sand 123 s and the main failure occurred at 140 s e AEsignal had strong responses at these three time points and itwas stronger at 75 s than that at 123 s Interestingly as shownin Figure 4(f ) the EMR signal met its valley values around75 s 123 s and 140 s It is most striking around 123 sMeanwhile in Figure 4(h) the EMR signal met its significantmutation response around 123 s while the response is lessremarkable around 75 s and 140 s Compared with Sample 1the overall electric-magnetic signal strength was significantlyweaker In particular the high-frequency magnetic signalwas not only weak but also poorly corresponding to thestress and AE signal

e variation law of low-frequency electric signal wassimilar to that of Sample 1 e signals of channel 2 (ch2Figure 5(b)) and channel 9 (ch9 Figure 5(d)) changed onlyslightly about 1mV before the occurrence of main fractureBy contrast they changed significantly after the main failuredeveloped Because of the higher sensitivity the electricsignal of channel 8 (ch8 Figure 5(c)) fluctuated greatly whenstress began to change at 75 s and it presented the secondchange at 123 s when the overall basic value had reducedis implied that the internal failure at 75 s brings aboutsome negative charges surrounding the 8 test point Be-cause of the weak electroconductivity of the rock this po-tential remained constant until the abundant new chargesformed at the second fracture site (123 s) When the mainfailure occurred at 140 s the amplitude of signal fluctuationof channel 8 reached the maximum but this was still smallerthan that of Sample 1 is indicated that sample size couldaffect intensity of the electric signal but they had consistentvariation tendency

4 Discussion

41 Electric-Magnetic Signal Generation Mechanism evariable motion of charges is an important way to generatethe electric-magnetic wave and includes two mechanismssuch as vibration or transition of electric dipole and re-laxation of separated charges Most mechanisms of EMR

Figure 1 Experimental system

Advances in Materials Science and Engineering 3

generation induced by deformation and failure of coal orrock are related to development of cracks One is asymmetriccharges along the axial direction of cracks for exampleelectric dipole model e other is positive and negativecharges generated on cracks wall such as variable motion ofcharges and relaxation of separated charges caused byfriction electrification or piezoelectric effect erefore it isnecessary to study how charges are generated and movedwhen exploring the mechanism of EMR generation uponstress failure of coal or rock

In these experiments the rock suffered shear failurewhich is different from tensional failure erefore there isresidual stress on crack surfaces even after sufficient slidingof these surfaces Such residual frictional resistance could beregarded as the main source of stress Meanwhile the energyrelease rate of shear failure was two magnitudes higher than

that of tensional failure In other words shear failure re-leased an increased concentration of energy at the failurewhich was related to different development processes ofshear cracks and tensional cracks at the end point

In the shearing process charges of different polaritieswould be generated on the upper and lower shear surfaceswhich were attributed to piezoelectric effect frictional effectand asymmetric breakages of crystal bonds (Figure 6)

Charge generation induced by the piezoelectric effect ismainly manifested during growth of cracks With the ex-tension of cracks the stress of microunit on the uppersurface of cracks changes significantly thus attractingcharges to some microunits containing piezoelectric mate-rials After further extension of the cracks these microunitsare distributed on the upper and lower surfaces of the cracksmaking both upper and lower surfaces charged When themain crack was cut through (ie the failure of materials)charges generated by the piezoelectric effect are reducedwhich would contribute less to EMR signals

EMR signal induced by triboelectric charge existsthroughout the whole shear failure However its contributionsare different in different stages During the early loading perioddue to the small pressure stress the relative displacementbetween upper and lower surfaces of the cracks was very smalland the electrification by friction was relatively weak Never-theless the relative displacement between upper and lowersurfaces increased significantly after the principal crack was cutthrough accompanied by strong friction effect and increasedgeneration of charges both of which contributed to increasedgeneration of EMR signals Meanwhile the contributions offriction effect to the EMR signal under shear failure changedwith the shear angle Obviously friction played a greater roleunder a small shear angle and high-pressure stress

ese effects influence the whole shear failure processtogether resulting in the continuous accumulation of chargeson the upper and lower crack surfaces Moreover rock ma-terials are of poor conductive features which have low rate ofcharge release Charges in rockmaterials will not disappear in ashort period but instead move with the surface displacementBecause the total charge on crack surface increases continu-ously the electric signal strengthens gradually in the wholefailure process when viewed from the macroscopic perspectiveBesides the distance between the testing point and chargeschanged when upper and lower surfaces had relative dis-placement thus causing the pulse fluctuation of the electricsignal is conforms to the variation law of the electric signal

(a) (b) (c)

Figure 2 Sensors (a) Electrode (b) AE sensor (c) Ferrite rod antenna

1ndash3 Electrodes4 AE sensor5 Ferrite rod antenna

5

34

2

1

5

a

B

A

Figure 3 Shearing equipment 1ndash3 electrodes 4 AE sensor 5 ferriterod antenna

4 Advances in Materials Science and Engineering

0

10

20

30

40

50St

ress

(MPa

)

Load value

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(a)

ndash8

ndash6

ndash4

ndash2

0

2

4

6

Electric-ch2

Elec

tric

(mV

)

30 60 90 120 150 1800Time (s)

(b)

Electric-ch8

Elec

tric

(mV

)

18060 90 120 150300Time (s)

ndash30

ndash20

ndash10

0

10

20

30

(c)

Electric-ch9

Elec

tric

(mV

)

ndash10

ndash05

00

05

10

15

20

25

30

35

30 60 90 120 150 1800Time (s)

(d)

Ener

gy (m

J)

AE-ch2

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

ndash20000

0

20000

40000

60000

80000

100000

120000

140000

160000

(e)

Ener

gy (m

J)

EMR (1kHz)-ch5

0

500

1000

1500

2000

2500

3000

3500

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(f )

Figure 4 Continued

Advances in Materials Science and Engineering 5

observed in the experiments Furthermore the motion ofcharges generates the EMR signal

42 Correlation of Various Signals At present most scholarsaccept that sample damages and failures could be analyzed byvariation of stress and AE signal If the high correlationbetween electric-magnetic signals and stress as well as AEcould be proved it would lay foundations for using electric-magnetic signals to analyze sample damage and dynamicdisasters of coal or rock Based on the aforementionedanalysis we found that there is certain correlation betweenelectric-magnetic signals and stress as well as AE Meanwhilethe correlation between EMR signal of conventional fre-quency and AE as well as stress has been recognized by mostscholars However no quantitative evaluation index wasproposed for such correlation In this paper the correlationcoefficient (|r|) between electric-magnetic signals and stressas well as AE was calculated using the Origin mathematicalsoftware which was used to evaluate their consistency

Take the correlation between stress and electric signal(Figure 7(a)) for example It demonstrated low linear cor-relation between two signals when the calculated maximumcorrelation coefficient |r|lt 04 significant correlation when04le |r|lt 07 and high linear correlation when 07le |r|lt 1When the delay (τ) corresponding to the maximum cor-relation coefficient is negative stress changes earlier than theelectric signal otherwise the electric signal changes earlier

e calculated correlation coefficient between electric-magnetic signals of Sample 1 and stress as well as AE isshown in Figure 7 In most cases τ is close to 0 but in somecases τ is not 0 Corresponding to the maximum correlationcoefficient between stress and electric signal of channel 8(Figure 7(a)) τ was 10 s indicating that electric signalchanged earlier than stress However the electric signal dataof channel 9 lagged for 2 s behind the stress (Figure 7(a)) In

Figure 7(d) the delay between the magnetic signal ofchannel 5 and channel 8 and AE signal of channel 2 was 2 sindicating that the EMR signal changed earlier than the AEsignal Besides correlation coefficients of electric signal hadpositive and negative values which were related to accu-mulation of positive and negative charges in the electroderegion A similar phenomenon was observed in correlationcoefficients of Sample 2 (Table 1) Meanwhile we calculatedanother experimental data other than those used in thispaper According to various estimates the correlation co-efficient between electric signal and stress might be eitherpositive or negative at equivalent probability is was alsocaused by different charge polarities of different regionsupon deformation or failure of the rockWhenmore positivecharges accumulate in one region the local electric signalincreased generally forming a positive correlation withstress variation Otherwise more negative charges accu-mulate resulting in the negative correlation between theelectric signal and stress

Table 1 presents peak correlation coefficients of signalsfrom Samples 1 and 2 Based on a comparison of 12 groupscorrelation coefficients between electric-magnetic signalsand stress were higher than those between electric-magneticsignals and AE in eight groups correlation coefficients wereclose to those between electric-magnetic signals and AE intwo groups and correlation coefficients were smaller in twogroups With respect to correlation coefficients betweenstress and electric-magnetic signals there were high linearcorrelation (in 6 groups) significant correlation (in 3groups) and low linear correlation (in 3 groups) Howeverconcerning the correlation coefficients between AE andelectric-magnetic signals there were no high linear corre-lation significant correlation (in 9 groups) and low linearcorrelation (in 3 groups) erefore the correlation betweenmagnetic signal and stress as well as AE was superior to thatof the electric signal

ndash20 0 20 40 60 80 100 120 140 160 180 200

0

100

200

300

400

500

600En

ergy

(mJ)

Time (s)

EMR (5kHz)-ch7

(g)

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140 160 180 200

800

1000

1200

1400

1600

1800

2000

Time (s)

EMR (300kHz)-ch8

(h)

Figure 4 Electric-magnetic-acoustic signals of 1 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

6 Advances in Materials Science and Engineering

0

10

20

30

40

50

Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

Load value

(a)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

ndash2

0

2

4

6

8

Electric-ch2

(b)

Elec

tric

(mV

)

ndash200

ndash100

0

100

200

300

400

Electric-ch8

ndash20 0 20 40 60 80 100 120 140 160Time (s)

(c)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

10

15

20

ndash5

0

5

25

30

35

Electric-ch9

(d)

0

20000

40000

60000

80000

100000

Ener

gy (m

J)

AE-ch2

ndash20 0 20 40 60 80 100 120 140Time (s)

(e)

0

50

100

150

200

250

300

EMR (1kHz)-ch5

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140Time (s)

(f )

Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

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Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

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ate

ria

ls

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Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

generation induced by deformation and failure of coal orrock are related to development of cracks One is asymmetriccharges along the axial direction of cracks for exampleelectric dipole model e other is positive and negativecharges generated on cracks wall such as variable motion ofcharges and relaxation of separated charges caused byfriction electrification or piezoelectric effect erefore it isnecessary to study how charges are generated and movedwhen exploring the mechanism of EMR generation uponstress failure of coal or rock

In these experiments the rock suffered shear failurewhich is different from tensional failure erefore there isresidual stress on crack surfaces even after sufficient slidingof these surfaces Such residual frictional resistance could beregarded as the main source of stress Meanwhile the energyrelease rate of shear failure was two magnitudes higher than

that of tensional failure In other words shear failure re-leased an increased concentration of energy at the failurewhich was related to different development processes ofshear cracks and tensional cracks at the end point

In the shearing process charges of different polaritieswould be generated on the upper and lower shear surfaceswhich were attributed to piezoelectric effect frictional effectand asymmetric breakages of crystal bonds (Figure 6)

Charge generation induced by the piezoelectric effect ismainly manifested during growth of cracks With the ex-tension of cracks the stress of microunit on the uppersurface of cracks changes significantly thus attractingcharges to some microunits containing piezoelectric mate-rials After further extension of the cracks these microunitsare distributed on the upper and lower surfaces of the cracksmaking both upper and lower surfaces charged When themain crack was cut through (ie the failure of materials)charges generated by the piezoelectric effect are reducedwhich would contribute less to EMR signals

EMR signal induced by triboelectric charge existsthroughout the whole shear failure However its contributionsare different in different stages During the early loading perioddue to the small pressure stress the relative displacementbetween upper and lower surfaces of the cracks was very smalland the electrification by friction was relatively weak Never-theless the relative displacement between upper and lowersurfaces increased significantly after the principal crack was cutthrough accompanied by strong friction effect and increasedgeneration of charges both of which contributed to increasedgeneration of EMR signals Meanwhile the contributions offriction effect to the EMR signal under shear failure changedwith the shear angle Obviously friction played a greater roleunder a small shear angle and high-pressure stress

ese effects influence the whole shear failure processtogether resulting in the continuous accumulation of chargeson the upper and lower crack surfaces Moreover rock ma-terials are of poor conductive features which have low rate ofcharge release Charges in rockmaterials will not disappear in ashort period but instead move with the surface displacementBecause the total charge on crack surface increases continu-ously the electric signal strengthens gradually in the wholefailure process when viewed from the macroscopic perspectiveBesides the distance between the testing point and chargeschanged when upper and lower surfaces had relative dis-placement thus causing the pulse fluctuation of the electricsignal is conforms to the variation law of the electric signal

(a) (b) (c)

Figure 2 Sensors (a) Electrode (b) AE sensor (c) Ferrite rod antenna

1ndash3 Electrodes4 AE sensor5 Ferrite rod antenna

5

34

2

1

5

a

B

A

Figure 3 Shearing equipment 1ndash3 electrodes 4 AE sensor 5 ferriterod antenna

4 Advances in Materials Science and Engineering

0

10

20

30

40

50St

ress

(MPa

)

Load value

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(a)

ndash8

ndash6

ndash4

ndash2

0

2

4

6

Electric-ch2

Elec

tric

(mV

)

30 60 90 120 150 1800Time (s)

(b)

Electric-ch8

Elec

tric

(mV

)

18060 90 120 150300Time (s)

ndash30

ndash20

ndash10

0

10

20

30

(c)

Electric-ch9

Elec

tric

(mV

)

ndash10

ndash05

00

05

10

15

20

25

30

35

30 60 90 120 150 1800Time (s)

(d)

Ener

gy (m

J)

AE-ch2

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

ndash20000

0

20000

40000

60000

80000

100000

120000

140000

160000

(e)

Ener

gy (m

J)

EMR (1kHz)-ch5

0

500

1000

1500

2000

2500

3000

3500

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(f )

Figure 4 Continued

Advances in Materials Science and Engineering 5

observed in the experiments Furthermore the motion ofcharges generates the EMR signal

42 Correlation of Various Signals At present most scholarsaccept that sample damages and failures could be analyzed byvariation of stress and AE signal If the high correlationbetween electric-magnetic signals and stress as well as AEcould be proved it would lay foundations for using electric-magnetic signals to analyze sample damage and dynamicdisasters of coal or rock Based on the aforementionedanalysis we found that there is certain correlation betweenelectric-magnetic signals and stress as well as AE Meanwhilethe correlation between EMR signal of conventional fre-quency and AE as well as stress has been recognized by mostscholars However no quantitative evaluation index wasproposed for such correlation In this paper the correlationcoefficient (|r|) between electric-magnetic signals and stressas well as AE was calculated using the Origin mathematicalsoftware which was used to evaluate their consistency

Take the correlation between stress and electric signal(Figure 7(a)) for example It demonstrated low linear cor-relation between two signals when the calculated maximumcorrelation coefficient |r|lt 04 significant correlation when04le |r|lt 07 and high linear correlation when 07le |r|lt 1When the delay (τ) corresponding to the maximum cor-relation coefficient is negative stress changes earlier than theelectric signal otherwise the electric signal changes earlier

e calculated correlation coefficient between electric-magnetic signals of Sample 1 and stress as well as AE isshown in Figure 7 In most cases τ is close to 0 but in somecases τ is not 0 Corresponding to the maximum correlationcoefficient between stress and electric signal of channel 8(Figure 7(a)) τ was 10 s indicating that electric signalchanged earlier than stress However the electric signal dataof channel 9 lagged for 2 s behind the stress (Figure 7(a)) In

Figure 7(d) the delay between the magnetic signal ofchannel 5 and channel 8 and AE signal of channel 2 was 2 sindicating that the EMR signal changed earlier than the AEsignal Besides correlation coefficients of electric signal hadpositive and negative values which were related to accu-mulation of positive and negative charges in the electroderegion A similar phenomenon was observed in correlationcoefficients of Sample 2 (Table 1) Meanwhile we calculatedanother experimental data other than those used in thispaper According to various estimates the correlation co-efficient between electric signal and stress might be eitherpositive or negative at equivalent probability is was alsocaused by different charge polarities of different regionsupon deformation or failure of the rockWhenmore positivecharges accumulate in one region the local electric signalincreased generally forming a positive correlation withstress variation Otherwise more negative charges accu-mulate resulting in the negative correlation between theelectric signal and stress

Table 1 presents peak correlation coefficients of signalsfrom Samples 1 and 2 Based on a comparison of 12 groupscorrelation coefficients between electric-magnetic signalsand stress were higher than those between electric-magneticsignals and AE in eight groups correlation coefficients wereclose to those between electric-magnetic signals and AE intwo groups and correlation coefficients were smaller in twogroups With respect to correlation coefficients betweenstress and electric-magnetic signals there were high linearcorrelation (in 6 groups) significant correlation (in 3groups) and low linear correlation (in 3 groups) Howeverconcerning the correlation coefficients between AE andelectric-magnetic signals there were no high linear corre-lation significant correlation (in 9 groups) and low linearcorrelation (in 3 groups) erefore the correlation betweenmagnetic signal and stress as well as AE was superior to thatof the electric signal

ndash20 0 20 40 60 80 100 120 140 160 180 200

0

100

200

300

400

500

600En

ergy

(mJ)

Time (s)

EMR (5kHz)-ch7

(g)

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140 160 180 200

800

1000

1200

1400

1600

1800

2000

Time (s)

EMR (300kHz)-ch8

(h)

Figure 4 Electric-magnetic-acoustic signals of 1 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

6 Advances in Materials Science and Engineering

0

10

20

30

40

50

Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

Load value

(a)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

ndash2

0

2

4

6

8

Electric-ch2

(b)

Elec

tric

(mV

)

ndash200

ndash100

0

100

200

300

400

Electric-ch8

ndash20 0 20 40 60 80 100 120 140 160Time (s)

(c)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

10

15

20

ndash5

0

5

25

30

35

Electric-ch9

(d)

0

20000

40000

60000

80000

100000

Ener

gy (m

J)

AE-ch2

ndash20 0 20 40 60 80 100 120 140Time (s)

(e)

0

50

100

150

200

250

300

EMR (1kHz)-ch5

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140Time (s)

(f )

Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

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Chemistry

Analytical ChemistryInternational Journal of

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ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

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Hindawiwwwhindawicom Volume 2018

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High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

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Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

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BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

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ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

0

10

20

30

40

50St

ress

(MPa

)

Load value

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(a)

ndash8

ndash6

ndash4

ndash2

0

2

4

6

Electric-ch2

Elec

tric

(mV

)

30 60 90 120 150 1800Time (s)

(b)

Electric-ch8

Elec

tric

(mV

)

18060 90 120 150300Time (s)

ndash30

ndash20

ndash10

0

10

20

30

(c)

Electric-ch9

Elec

tric

(mV

)

ndash10

ndash05

00

05

10

15

20

25

30

35

30 60 90 120 150 1800Time (s)

(d)

Ener

gy (m

J)

AE-ch2

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

ndash20000

0

20000

40000

60000

80000

100000

120000

140000

160000

(e)

Ener

gy (m

J)

EMR (1kHz)-ch5

0

500

1000

1500

2000

2500

3000

3500

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(f )

Figure 4 Continued

Advances in Materials Science and Engineering 5

observed in the experiments Furthermore the motion ofcharges generates the EMR signal

42 Correlation of Various Signals At present most scholarsaccept that sample damages and failures could be analyzed byvariation of stress and AE signal If the high correlationbetween electric-magnetic signals and stress as well as AEcould be proved it would lay foundations for using electric-magnetic signals to analyze sample damage and dynamicdisasters of coal or rock Based on the aforementionedanalysis we found that there is certain correlation betweenelectric-magnetic signals and stress as well as AE Meanwhilethe correlation between EMR signal of conventional fre-quency and AE as well as stress has been recognized by mostscholars However no quantitative evaluation index wasproposed for such correlation In this paper the correlationcoefficient (|r|) between electric-magnetic signals and stressas well as AE was calculated using the Origin mathematicalsoftware which was used to evaluate their consistency

Take the correlation between stress and electric signal(Figure 7(a)) for example It demonstrated low linear cor-relation between two signals when the calculated maximumcorrelation coefficient |r|lt 04 significant correlation when04le |r|lt 07 and high linear correlation when 07le |r|lt 1When the delay (τ) corresponding to the maximum cor-relation coefficient is negative stress changes earlier than theelectric signal otherwise the electric signal changes earlier

e calculated correlation coefficient between electric-magnetic signals of Sample 1 and stress as well as AE isshown in Figure 7 In most cases τ is close to 0 but in somecases τ is not 0 Corresponding to the maximum correlationcoefficient between stress and electric signal of channel 8(Figure 7(a)) τ was 10 s indicating that electric signalchanged earlier than stress However the electric signal dataof channel 9 lagged for 2 s behind the stress (Figure 7(a)) In

Figure 7(d) the delay between the magnetic signal ofchannel 5 and channel 8 and AE signal of channel 2 was 2 sindicating that the EMR signal changed earlier than the AEsignal Besides correlation coefficients of electric signal hadpositive and negative values which were related to accu-mulation of positive and negative charges in the electroderegion A similar phenomenon was observed in correlationcoefficients of Sample 2 (Table 1) Meanwhile we calculatedanother experimental data other than those used in thispaper According to various estimates the correlation co-efficient between electric signal and stress might be eitherpositive or negative at equivalent probability is was alsocaused by different charge polarities of different regionsupon deformation or failure of the rockWhenmore positivecharges accumulate in one region the local electric signalincreased generally forming a positive correlation withstress variation Otherwise more negative charges accu-mulate resulting in the negative correlation between theelectric signal and stress

Table 1 presents peak correlation coefficients of signalsfrom Samples 1 and 2 Based on a comparison of 12 groupscorrelation coefficients between electric-magnetic signalsand stress were higher than those between electric-magneticsignals and AE in eight groups correlation coefficients wereclose to those between electric-magnetic signals and AE intwo groups and correlation coefficients were smaller in twogroups With respect to correlation coefficients betweenstress and electric-magnetic signals there were high linearcorrelation (in 6 groups) significant correlation (in 3groups) and low linear correlation (in 3 groups) Howeverconcerning the correlation coefficients between AE andelectric-magnetic signals there were no high linear corre-lation significant correlation (in 9 groups) and low linearcorrelation (in 3 groups) erefore the correlation betweenmagnetic signal and stress as well as AE was superior to thatof the electric signal

ndash20 0 20 40 60 80 100 120 140 160 180 200

0

100

200

300

400

500

600En

ergy

(mJ)

Time (s)

EMR (5kHz)-ch7

(g)

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140 160 180 200

800

1000

1200

1400

1600

1800

2000

Time (s)

EMR (300kHz)-ch8

(h)

Figure 4 Electric-magnetic-acoustic signals of 1 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

6 Advances in Materials Science and Engineering

0

10

20

30

40

50

Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

Load value

(a)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

ndash2

0

2

4

6

8

Electric-ch2

(b)

Elec

tric

(mV

)

ndash200

ndash100

0

100

200

300

400

Electric-ch8

ndash20 0 20 40 60 80 100 120 140 160Time (s)

(c)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

10

15

20

ndash5

0

5

25

30

35

Electric-ch9

(d)

0

20000

40000

60000

80000

100000

Ener

gy (m

J)

AE-ch2

ndash20 0 20 40 60 80 100 120 140Time (s)

(e)

0

50

100

150

200

250

300

EMR (1kHz)-ch5

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140Time (s)

(f )

Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

observed in the experiments Furthermore the motion ofcharges generates the EMR signal

42 Correlation of Various Signals At present most scholarsaccept that sample damages and failures could be analyzed byvariation of stress and AE signal If the high correlationbetween electric-magnetic signals and stress as well as AEcould be proved it would lay foundations for using electric-magnetic signals to analyze sample damage and dynamicdisasters of coal or rock Based on the aforementionedanalysis we found that there is certain correlation betweenelectric-magnetic signals and stress as well as AE Meanwhilethe correlation between EMR signal of conventional fre-quency and AE as well as stress has been recognized by mostscholars However no quantitative evaluation index wasproposed for such correlation In this paper the correlationcoefficient (|r|) between electric-magnetic signals and stressas well as AE was calculated using the Origin mathematicalsoftware which was used to evaluate their consistency

Take the correlation between stress and electric signal(Figure 7(a)) for example It demonstrated low linear cor-relation between two signals when the calculated maximumcorrelation coefficient |r|lt 04 significant correlation when04le |r|lt 07 and high linear correlation when 07le |r|lt 1When the delay (τ) corresponding to the maximum cor-relation coefficient is negative stress changes earlier than theelectric signal otherwise the electric signal changes earlier

e calculated correlation coefficient between electric-magnetic signals of Sample 1 and stress as well as AE isshown in Figure 7 In most cases τ is close to 0 but in somecases τ is not 0 Corresponding to the maximum correlationcoefficient between stress and electric signal of channel 8(Figure 7(a)) τ was 10 s indicating that electric signalchanged earlier than stress However the electric signal dataof channel 9 lagged for 2 s behind the stress (Figure 7(a)) In

Figure 7(d) the delay between the magnetic signal ofchannel 5 and channel 8 and AE signal of channel 2 was 2 sindicating that the EMR signal changed earlier than the AEsignal Besides correlation coefficients of electric signal hadpositive and negative values which were related to accu-mulation of positive and negative charges in the electroderegion A similar phenomenon was observed in correlationcoefficients of Sample 2 (Table 1) Meanwhile we calculatedanother experimental data other than those used in thispaper According to various estimates the correlation co-efficient between electric signal and stress might be eitherpositive or negative at equivalent probability is was alsocaused by different charge polarities of different regionsupon deformation or failure of the rockWhenmore positivecharges accumulate in one region the local electric signalincreased generally forming a positive correlation withstress variation Otherwise more negative charges accu-mulate resulting in the negative correlation between theelectric signal and stress

Table 1 presents peak correlation coefficients of signalsfrom Samples 1 and 2 Based on a comparison of 12 groupscorrelation coefficients between electric-magnetic signalsand stress were higher than those between electric-magneticsignals and AE in eight groups correlation coefficients wereclose to those between electric-magnetic signals and AE intwo groups and correlation coefficients were smaller in twogroups With respect to correlation coefficients betweenstress and electric-magnetic signals there were high linearcorrelation (in 6 groups) significant correlation (in 3groups) and low linear correlation (in 3 groups) Howeverconcerning the correlation coefficients between AE andelectric-magnetic signals there were no high linear corre-lation significant correlation (in 9 groups) and low linearcorrelation (in 3 groups) erefore the correlation betweenmagnetic signal and stress as well as AE was superior to thatof the electric signal

ndash20 0 20 40 60 80 100 120 140 160 180 200

0

100

200

300

400

500

600En

ergy

(mJ)

Time (s)

EMR (5kHz)-ch7

(g)

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140 160 180 200

800

1000

1200

1400

1600

1800

2000

Time (s)

EMR (300kHz)-ch8

(h)

Figure 4 Electric-magnetic-acoustic signals of 1 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

6 Advances in Materials Science and Engineering

0

10

20

30

40

50

Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

Load value

(a)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

ndash2

0

2

4

6

8

Electric-ch2

(b)

Elec

tric

(mV

)

ndash200

ndash100

0

100

200

300

400

Electric-ch8

ndash20 0 20 40 60 80 100 120 140 160Time (s)

(c)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

10

15

20

ndash5

0

5

25

30

35

Electric-ch9

(d)

0

20000

40000

60000

80000

100000

Ener

gy (m

J)

AE-ch2

ndash20 0 20 40 60 80 100 120 140Time (s)

(e)

0

50

100

150

200

250

300

EMR (1kHz)-ch5

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140Time (s)

(f )

Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

0

10

20

30

40

50

Stre

ss (M

Pa)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

Load value

(a)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

ndash2

0

2

4

6

8

Electric-ch2

(b)

Elec

tric

(mV

)

ndash200

ndash100

0

100

200

300

400

Electric-ch8

ndash20 0 20 40 60 80 100 120 140 160Time (s)

(c)

Elec

tric

(mV

)

ndash20 0 20 40 60 80 100 120 140 160Time (s)

10

15

20

ndash5

0

5

25

30

35

Electric-ch9

(d)

0

20000

40000

60000

80000

100000

Ener

gy (m

J)

AE-ch2

ndash20 0 20 40 60 80 100 120 140Time (s)

(e)

0

50

100

150

200

250

300

EMR (1kHz)-ch5

Ener

gy (m

J)

ndash20 0 20 40 60 80 100 120 140Time (s)

(f )

Figure 5 Continued

Advances in Materials Science and Engineering 7

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

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Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

It has to be pointed out that because correlation co-efficient is calculated based on linear correlation calculationthe correlation coefficients between the data that seemscorrelated are low in reality Figure 8 presents a comparisonbetween AE energy and the electric signals of ch8 eelectric signal enhanced when the AE signal strengthenedindicating the strong correlation between themWe believedthat such correlation might be nonlinear which explains thesmaller calculated correlation coefficient

43 Acoustic-Electric Coupling Model and VerificationFrom Figure 8 it could be seen that AE and electric signalswere correlated with each other As shown in Figure 8 atmost moments the acoustic emissions energy and electricvalues are relatively stable with some fluctuation At somemoments when there is a relatively significant damageoccurring inside the coal body (it is recorded that there is

the pulsed increase of acoustic emission energy whichindicates a relatively significant microrupture inside thesample) the electric signal increases suddenly which iscooperative with the acoustic emission energy e re-sponse is correlated especially when the sample rupturesand both the electric signal and the acoustic emissionsignal exhibit a rapid increase to the maximum value evariation mechanism of the electric signal can be viewedas follows the increase of electric signals results fromcharge accumulation during the loaded failure whereastheir decrease results from deprivation of charges lostgradually e speed of increase and decrease is also re-lated to the coupling capacitance between electrode andsamples Based on the aforementioned theory a circuitmodel was established for electric signal variation duringshear failure of the rock (Figure 9)

In this model the condenser voltage signal (the observedsignal) is correlated with signal source (S) resistance to

0

50

100

150

200En

ergy

(mJ)

EMR (5kHz)-ch7

ndash20 0 20 40 60 80 100 120 140Time (s)

(g)

Ener

gy (m

J)

0

10

20

30

40

50

60

EMR (300kHz)-ch8

ndash20 0 20 40 60 80 100 120 140Time (s)

(h)

Figure 5 Electric-magnetic-acoustic signals of 2 rock sample (1mmmin) (a) Stress-time Electric signals of (b) ch2 (c) ch8 and (d) ch9(e) Acoustic emission signals Magnetic signals of (f ) ch5 (g) ch7 and (h) ch8

+ ndash+ ndash

+ ndash+ ndash

+q ndashq

Figure 6 Direction of the electromagnetic field in shear failure

8 Advances in Materials Science and Engineering

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

Table 1 Statistics on correlation coefficient values between two indexes of electric-magnetic signals as well as stress and AE energy

Sample number Channel numberCorrelation coefficients between two indexes

Electric-stress Electric-AE EMR-stress EMR-AE

1

Ch2 0345 0357 mdash mdashCh8 minus0785 minus0535 mdash mdashCh9 0550 0570 mdash mdashCh5 mdash mdash 0711 0506Ch7 mdash mdash 0301 0540Ch8 mdash mdash 0679 0481

2

Ch2 minus0855 minus0406 mdash mdashCh8 minus0601 minus0193 mdash mdashCh9 0137 0386 mdash mdashCh5 mdash mdash 0925 0452Ch7 mdash mdash 0867 0421Ch8 mdash mdash 0772 0411

ndash150 ndash100 ndash50 0 50 100 150ndash10

ndash08

ndash06

ndash04

ndash02

00

02

04

06

08

10Co

rrel

atio

n co

effic

ient

Time (s)

Correlation of stress and electric-ch2 Correlation of stress and electric-ch8Correlation of stress and electric-ch9

(a)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

ndash06

ndash04

ndash02

00

02

04

06

08

10

Time (s)

Correlation of AE-ch2 and electric-ch2Correlation of AE-ch2 and electric-ch8Correlation of AE-ch2 and electric-ch9

(b)

Corr

elat

ion

coef

ficie

nt

ndash150 ndash100 ndash50 0 50 100 150

00

02

04

06

08

10

Time (s)

Correlation of stress and EMR (1kHz)-ch5

Correlation of stress and EMR (300kHz)-ch8 Correlation of stress and EMR (5kHz)-ch7

(c)

Corr

elat

ion

coef

ficie

nt

ndash200 ndash150 ndash100 ndash50 0 50 100 150 200

00

01

02

03

04

05

06

07

Time (s)

Correlation of AE-ch2 and EMR (1kHz)-ch5 Correlation of AE-ch2 and EMR (5kHz)-ch7 Correlation of AE-ch2 and EMR (300kHz)-ch8

(d)

Figure 7 Correlation coefficient of signals (sample 1) (a) Stress vs electric signals (b) AE energy vs electric signals (c) Stress vs EMRenergy (d) AE energy vs EMR energy

Advances in Materials Science and Engineering 9

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

ground (R) and capacitance (C) e following chargebalance exists

1113946t1

t0

a times EminusU

R1113874 11138751113874 1113875dt Ut1

minusUt01113872 1113873 times C (1)

where E represents the accumulated AE energy a representsthe ratio between electric charge quantity and accumulatedAE energy and U denotes the voltage of the condenser

Size of S is related to generation and development ofcracks which is proportional to AE energy Accumulated AEenergy in Δt is Ee quantity of electric charge generated bycracks is ql a times E and the quantity of electric charge re-leased to ground is qs ((Ut1

+ Ut0)2R) e overall charge

balance can be simplified as

aEminusUt1

+ Ut0

2R Ut1minusUt0

1113872 1113873 times C

aE Ut1C +

12R

1113874 1113875minusUt0Cminus

12R

1113874 1113875

2aR

C + 2RE Ut1minusUt0

timesCminus 2R

C + 2R

(2)

Let b (2aR(C + 2R)) and c ((Cminus 2R)(C + 2R))equation (2) can be expressed as follows

bE Ut1minus cUt0

(3)

Using equation (3) the collected electric signal wasconverted through adjusting c and its correlation with AE isdisplayed in Figure 10

As shown in Figure 10 the evolution characteristicsof AE energy and converted electric signal response aresimilar and cooperative For example in the majority ofmoments the AE energy and converted electric valuesare low and stable in Figure 10(a) Around 17 s and 24 sboth of them show growth spurt Around 100 s and 116 sthe cooperative anomalous characteristics are moresignificant At 171 s both values reach their maximumvalues cooperatively Hence there is a strong correlationexits between AE energy and electric signal with bothshowing a similar variation tendency which will layfoundations for further interpreting the generationmechanism of the electric signal by improving itsapplications

Ener

gy (m

J)

ndash200000

20000400006000080000

100000120000140000160000

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

AE-ch2Electric-ch9

ndash10ndash050005101520253035

Elec

tric

(mV

)

(a)

Ener

gy (m

J)

AE-ch2Electric-ch9

ndash200000

20000400006000080000

100000120000140000160000

ndash30

ndash20

ndash10

0

10

20

30

Elec

tric

(mV

)

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

(b)

Figure 8 Comparison between AE energy and the electric signals of ch8 (a) Sample 1 (b) Sample 2 Light blue dotted lines and orangearrows indicate abnormal response of signals

C

RS+

Figure 9 Acoustic-electric coupling model

10 Advances in Materials Science and Engineering

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

5 Conclusions

In this paper the laboratory experiments of sandstonesamples under shear loading were carried out meanwhilethe electric-magnetic-acoustic signal regularity was mea-sured and analyzed comparativelye results were obtainedas followed

(1) e electric-magnetic-acoustic signals are generatedduring the shear failure of the rock e magneticsignal is highly correlated with stress and AE signalbut the electric signal changes randomly When themain failure occurs the amplitude of the electricsignal fluctuation is larger than that of magnetic andAE signals e strength of electric-magnetic-acoustic signals is basically proportional to the rockstrength the energy released from failure thenumber of cracks and so on

(2) e correlation coefficients between electric-magnetic signal and stress as well as AE are cal-culated and used for quantitative evaluation of thecorrelation degree between signals e significantor highly linear proportion between the electric-magnetic signal and stress as well as AE reaches75 e correlation degree between the electric-magnetic signal and stress as well as AE is evenhigher

(3) A coupling model between AE and electric signal isestablished in which the magnitude of electric signalis related to AE energy (E) resistance to ground (R)and other parameters ere is a good correlationbetween the electric signal and AE energy whichconfirms the variation law of the electric signal andverifies rationality of the model

Data Availability

e data used to support the findings of this study are in-cluded within the article

Conflicts of Interest

e authors declare that there are no conflicts of interestregarding the publication of this paper

Authorsrsquo Contributions

Huilin Jia and Yue Niu contributed equally to this work

Acknowledgments

We thank the English editing contribution to the paper byBenjamin Shaw Director Liwen Bianji (Edanz GroupChina) e authors gratefully acknowledge the supportprovided by the project funded by the general program of theNational Natural Science Foundation of China (51674254)and Priority Academic Program Development of JiangsuHigher Education Institutions and the Fundamental Re-search Fund for the Central Universities (nos 2014ZDPY23and 2015XKZD04)

References

[1] A Franco and A R Diaz ldquoe future challenges for ldquocleancoal technologiesrdquo joining efficiency increase and pollutantemission controlrdquo Energy vol 34 no 3 pp 348ndash354 2009

[2] L Quesada Carballo M D R Perez Perez D CantadorFernandez A Caballero Amores and J M FernandezRodrıguez ldquoOptimum particle size of treated calcites for CO2capture in a power plantrdquo Materials vol 12 no 8 p 12842019

[3] Q Shi and B Qin ldquoExperimental research on gel-stabilizedfoam designed to prevent and control spontaneous com-bustion of coalrdquo Fuel vol 254 article 115558 2019

[4] J Whyatt ldquoDynamic failure in deep coal recent trends and apath forwardrdquo in Proceedings of the 27th InternationalConference on Ground Control in Mining pp 29ndash31 Mor-gantown WV USA July 2008

[5] J Ahirwal and S K Maiti ldquoAssessment of soil properties ofdifferent land uses generated due to surface coal mining

ndash16ndash14ndash12ndash10ndash8ndash6ndash4ndash20246810121416

Conv

erte

d el

ectr

ic

0 20 40 60 80 100 120 140 160 180 200ndash20Time (s)

Electric-ch8

Ener

gy (m

J)

AE-ch2

020000400006000080000

100000120000140000160000180000200000220000240000260000

(a)

0

20000

40000

60000

80000

100000

120000

140000

20ndash20 40 60 80 100 120 1400Time (s)

ndash60

ndash40

ndash20

0

20

40

60

80

Conv

erte

d el

ectr

ic

Ener

gy (m

J)

Electric-ch8AE-ch2

(b)

Figure 10 Correlation between AE energy and converted electric signals

Advances in Materials Science and Engineering 11

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

activities in tropical sal (Shorea robusta) forest Indiardquo CA-TENA vol 140 pp 155ndash163 2016

[6] W Cheng X Hu J Xie and Y Zhao ldquoAn intelligent geldesigned to control the spontaneous combustion of coal fireprevention and extinguishing propertiesrdquo Fuel vol 210pp 826ndash835 2017

[7] S Polesek-Karczewska ldquoEstimation of the structure-relatedshare of radiation heat transfer in a carbonised packed coalbedrdquo Fuel vol 195 pp 243ndash252 2017

[8] D N Espinoza J-M Pereira M Vandamme P Dangla andS Vidal-Gilbert ldquoDesorption-induced shear failure of coalbed seams during gas depletionrdquo International Journal of CoalGeology vol 137 pp 142ndash151 2015

[9] W J Gale and R L Blackwood ldquoStress distributions and rockfailure around coal mine roadwaysrdquo International Journal ofRock Mechanics and Mining Sciences amp Geomechanics Ab-stracts vol 24 no 3 pp 165ndash173 1987

[10] Z-L Li X-Q He L-M Dou D-Z Song G-F Wang andX-L Xu ldquoInvestigating the mechanism and prevention ofcoal mine dynamic disasters by using dynamic cyclic loadingtestsrdquo Safety Science vol 115 pp 215ndash228 2019

[11] S Marland A Merchant and N Rowson ldquoDielectricproperties of coalrdquo Fuel vol 80 no 13 pp 1839ndash1849 2001

[12] T Shiotani M Ohtsu and K Ikeda ldquoDetection and evalu-ation of AE waves due to rock deformationrdquo Construction andBuilding Materials vol 15 no 5-6 pp 235ndash246 2001

[13] M Heap S Vinciguerra and P Meredith ldquoe evolution ofelastic moduli with increasing crack damage during cyclicstressing of a basalt from Mt Etna volcanordquo Tectonophysicsvol 471 no 1-2 pp 153ndash160 2009

[14] F-Q Su K-I Itakura G Deguchi and K Ohga ldquoMonitoringof coal fracturing in underground coal gasification by acousticemission techniquesrdquo Applied Energy vol 189 pp 142ndash1562017

[15] C Khazaei J Hazzard and R Chalaturnyk ldquoDamagequantification of intact rocks using acoustic emission energiesrecorded during uniaxial compression test and discrete ele-ment modelingrdquo Computers and Geotechnics vol 67pp 94ndash102 2015

[16] Y Liang Q Li Y Gu and Q Zou ldquoMechanical and acousticemission characteristics of rock effect of loading andunloading confining pressure at the postpeak stagerdquo Journalof Natural Gas Science and Engineering vol 44 pp 54ndash642017

[17] X Wang X Liu E Wang et al ldquoExperimental research of theAE responses and fracture evolution characteristics for sand-paraffin similar materialrdquo Construction and Building Mate-rials vol 132 pp 446ndash456 2017

[18] B Kong Z Li and E Wang ldquoFine characterization rockthermal damage by acoustic emission techniquerdquo Journal ofGeophysics and Engineering vol 15 no 1 pp 1ndash12 2017

[19] I Yamada K Masuda and H Mizutani ldquoElectromagneticand acoustic emission associated with rock fracturerdquo Physicsof the Earth and Planetary Interiors vol 57 no 1-2pp 157ndash168 1989

[20] M H Adams ldquoSome observations of electromagnetic signalsprior to California earthquakesrdquo Journal of Scientific Explo-ration vol 4 pp 137ndash152 1990

[21] A Misra R C Prasad V S Chauhan and B Srilakshmi ldquoAtheoretical model for the electromagnetic radiation emissionduring plastic deformation and crack propagation in metallicmaterialsrdquo International Journal of Fracture vol 145 no 2pp 99ndash121 2007

[22] F Freund and D Sornette ldquoElectro-magnetic earthquakebursts and critical rupture of peroxy bond networks in rocksrdquoTectonophysics vol 431 no 1ndash4 pp 33ndash47 2007

[23] S O Gade U Weiss M A Peter and M G R SauseldquoRelation of electromagnetic emission and crack dynamics inepoxy resin materialsrdquo Journal of Nondestructive Evaluationvol 33 no 4 pp 711ndash723 2014

[24] A Carpinteri G Lacidogna A Manuello G NiccoliniA Schiavi and A Agosto ldquoMechanical and electromagneticemissions related to stress-induced cracksrdquo ExperimentalTechniques vol 36 no 3 pp 53ndash64 2012

[25] E Wang H Jia D Song N Li and W Qian ldquoUse of ultra-low-frequency electromagnetic emission to monitor stressand failure in coal minesrdquo International Journal of RockMechanics and Mining Sciences vol 70 pp 16ndash25 2014

[26] E Wang X He J Wei B Nie and D Song ldquoElectromagneticemission graded warning model and its applications againstcoal rock dynamic collapsesrdquo International Journal of RockMechanics and Mining Sciences vol 48 no 4 pp 556ndash5642011

[27] B Kong E Wang Z Li and Y Niu ldquoTime-varying char-acteristics of electromagnetic radiation during the coal-heating processrdquo International Journal of Heat and MassTransfer vol 108 pp 434ndash442 2017

[28] Y Niu X Song Z Li et al ldquoStudy on EP response tocompression-induced damage of coal-measure rock and themechanism behind such responserdquo Journal of Geophysics andEngineering vol 16 no 1 pp 242ndash252 2019

[29] Y Niu C Wang E Wang and Z Li ldquoExperimental study onthe damage evolution of gas-bearing coal and its electricpotential responserdquo Rock Mechanics and Rock Engineeringpp 1ndash16 2019

[30] S Li S Hu B Xie et al ldquoInfluence of pleat geometry on thefiltration and cleaning characteristics of filter mediardquo Sepa-ration and Purification Technology vol 210 pp 38ndash47 2019

[31] F Freund ldquoCharge generation and propagation in igneousrocksrdquo Journal of Geodynamics vol 33 no 4-5 pp 543ndash5702002

[32] Z-H Li E-Y Wang Z-T Liu X-Y Song and Y-N LildquoStudy on characteristics and rules of surface potential duringcoal fracturerdquo Journal of China University of Mining ampTechnology vol 2 2009

[33] Z Li Y Niu E Wang et al ldquoExperimental study on electricpotential response characteristics of gas-bearing coal duringdeformation and fracturing processrdquo Processes vol 7 no 2p 72 2019

12 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom