an online technique for monitoring the insulation condition of ac machine stator windings

IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 20, NO. 4, DECEMBER 2005 737

An Online Technique for Monitoring the InsulationCondition of AC Machine Stator Windings

Sang Bin Lee, Member, IEEE, Karim Younsi, Senior Member, IEEE, and Gerald B. Kliman, Life Fellow, IEEE

Abstract—A novel online technique for monitoring the insula-tion condition of ac machine stator windings is proposed in thispaper. The concept is to measure the differential leakage currentsof each phase winding from the terminal box in a noninvasive man-ner to assess the insulation condition during motor operation. Theconventional differential CTs used for phase fault protection canbe replaced with high performance current sensors to measurethe leakage current with higher accuracy. Indicators for insulationcondition such as the capacitance and dissipation factor are calcu-lated based on the measurements to provide a low cost solution foronline insulation condition assessment. A simplified online insula-tion system model is derived for analysis and interpretation of themeasured data. Experimental results on a 15-hp induction motorunder simulated insulation degradation conditions show that theproposed technique is a very sensitive method capable of detectingincipient signs of insulation degradation.

Index Terms—AC machines, dielectric losses, fault diagnosis,insulation testing, leakage currents, monitoring .

I. INTRODUCTION

THE electrical insulation is one of the most critical compo-nents for operation of ac electric machines of all types and

sizes. It is shown in industrial surveys and other studies on ma-chine reliability [1]–[3] that the stator winding insulation is alsoone of the most vulnerable components used in an ac electricmachine. The surveys published in [1], [2] show that 30%–40%of ac machine failures are initiated from problems in the statorinsulation, and in a recent survey published in [3], it is shownthat the percentage of stator related failures is as high as 60%–70% for high voltage machines (generators and large motors).Stator insulation failure during machine operation can lead to acatastrophic machine failure resulting in a costly forced outage.Prevention of such an outage is a major concern for both the ma-chine manufacturer and end user, since it can result in significantloss of revenue during the outage as well as repair or replace-ment cost. Therefore, stator insulation quality assessment is animportant requirement, and there has been considerable effortover the last century in identifying the causes of stator insulationdegradation and failure, and finding methods for assessing thecondition of stator insulation systems. To increase the reliabil-ity of the machine and to reduce the chance of forced outages,periodic as well as online insulation tests have been developedover many years [4]–[7].

Manuscript received June 9, 2004; revised October 20, 2004. Paper no. TEC-00168-2004.

S. B. Lee is with the Department of Electrical Engineering, Korea University,Seoul, Korea (e-mail: [email protected]).

K. Younsi is with General Electric Company Global Research, Schenectady,NY 12309 USA.

G. B. Kliman, deceased, was with the Rensselaer Polytechnic Institute, Troy,NY 12180-3590 USA.

Digital Object Identifier 10.1109/TEC.2005.853760

A. Offline Stator Insulation Monitoring

The most accepted and widely used offline stator insulationtests include the insulation resistance (polarization index), highpotential (ac and dc), capacitance, dissipation factor (tip-up),surge comparison, and offline partial discharge tests, where eachtest is effective for diagnosing certain types of insulation prob-lems. The main limitation of offline testing is that the machinemust be removed from service. The machine outage intervaldepends on the machine and its application, but typically isonce every 3–6 years; therefore, the machine cannot be testedfrequently enough to guarantee reliable machine operation un-til the next outage. In addition, considering that most offlinetests listed above do not contain significant diagnostic informa-tion unless it is trended over time and measured under identicalconditions, it is very difficult to assess its present condition orpredict the remaining life of the insulation with offline data.Other shortcomings of offline tests are due to the fact that thewinding insulation is not exposed to actual operating stressesduring the test, and that some tests are invasive.

B. Online Stator Insulation Monitoring

If the insulation condition can be assessed online, more accu-rate and reliable diagnostic information on insulation conditionand its remaining life can be provided to the machine user oroperator. In addition, the measurements can be obtained underactual operating conditions without an outage with initial in-vestment for the dedicated sensors and a means of processingthe data for trending. The methods available for online sta-tor insulation monitoring include thermal monitoring, chemicalmonitoring (ozone, tagging compound monitoring), phase andground fault relays, and online partial discharge monitoring.The primary purpose of online thermal or chemical monitoringis to detect severe thermal problems in the insulation when in-sulation failure is imminent (they are only considered to be costeffective for large machines). Phase and ground fault relays areinstalled in a machine to prevent severe machine damage causedby insulation failure; however, they are of go/no go type mon-itoring and do not provide true monitoring capability. Onlinepartial discharge monitors can detect partial discharge activity,which is one of the most important symptoms of severe insula-tion degradation leading to failure [8]. Although online partialdischarge monitoring requires installation of dedicated sensorsand specialized equipment, and the interpretation is somewhatsubjective, it is a very effective means of monitoring and po-tentially preventing failures caused by corona activity driveninsulation aging.

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738 IEEE TRANSACTIONS ON ENERGY CONVERSION, VOL. 20, NO. 4, DECEMBER 2005

Corona (partial discharge) is not the only root cause of sta-tor insulation failure. Failures in the stator insulation systemare caused by a combination of multiple internal and externalstresses on the insulation system during machine operation (thecauses and mechanisms for stator insulation failure are describedin detail in [4] and [5]). The main root causes of insulation fail-ure that is common in random and form wound machines canbe summarized as:

1) delamination or cracking of insulation due to thermal over-load or cycling;

2) abrasion of insulation due to vibration of loose coils orabrasive particles;

3) degradation due to repetitive electrical stresses; and4) electrical tracking or chemical degradation due to contam-

ination.Partial discharge is one of the main symptoms of insulation

failure mechanisms, but cannot detect all the signs of insula-tion damage that leads to failure. Moreover, partial dischargeis a phenomenon observed only in high voltage (2300 V orabove) or inverter fed machines. Several techniques have beenreported for online insulation monitoring based on capacitanceand dissipation factor measurements; however, they are appli-cable to equipment such as bushings and transformers, or ca-bles [9]–[11].

Given the limitations of the state-of-the-art in this area andthe potential benefits of online insulation condition assessment,the objective of this work is to develop an effective and prac-tical technique that is capable of monitoring the overall con-dition of the stator winding insulation online. An overview ofoffline capacitance and dissipation factor tests are presented inSection II, which serves as a basis for the online version of thetests. The concept and potential benefits of the proposed tech-niques is presented in Section III along with the derivation of asimplified online insulation system model, which is used as thebasis for the algorithm and analysis. The details of the setup andresults obtained from a 15-hp motor for feasibility evaluationare presented in Section IV. Section V describes the challengesand practical issues for implementation and lists suggestions forfuture work, and the conclusions are drawn in Section VI.

II. OFFLINE CAPACITANCE AND DISSIPATION FACTOR

(tanδ)/POWER FACTOR TESTING

The online technique for insulation condition assessment pro-posed in this paper is based on measurement of the capacitanceand dissipation factor online. Therefore, the offline versions ofthe tests introduced in [4], [5], [12]–[14] are summarized hereas they can be used as the theoretical basis for analyzing onlinetest results.

The capacitance test measures the capacitance value betweenthe stator conductor and the grounded stator core using a ca-pacitance bridge [4], [5], [12]–[14]. If the capacitance measure-ment is trended over time, it can provide indications of thermaldeterioration, moisture absorption, and endwinding contamina-tion [4]. Thermal overheating of the insulation causes undesir-able delamination or drying out of the insulation that introducesair or gas within the insulation, which causes the capacitance

Fig. 1. (a) Electrical insulation system equivalent circuit. (b) Phasor diagramrepresentation of capacitive ad resistive currents.

to decrease (decrease in effective dielectric constant). On thecontrary, the value of the capacitance will increase if the insu-lation absorbs moisture, since the dielectric constant of wateris much higher than that of solid insulation. Contamination ofendwindings with conductive substances increases the effectivearea of coupling between the conductor and grounded statorcore, which results in a possible increase in the capacitance. Itis preferred that each phase is measured separately during of-fline testing for monitoring the condition of each phase, and tocompare the values between phases.

The dissipation (or power) factor test is often used in conjunc-tion with the capacitance test because they can provide valuableindications of insulation problems when combined. The dissi-pation factor, also known as the tan δ, is an indication of thedielectric losses in the groundwall insulation [4], [5], [12]–[14].The electrical equivalent circuit for the groundwall insulationsystem can be modeled as an equivalent capacitor, Ceq, that rep-resents capacitive coupling, and a resistor, Req, that representsdielectric losses as shown in Fig. 1(a). The measured leakagecurrent, I , consists of capacitive and resistive components, IC

and IR , with respect to the voltage, V , as shown in Fig. 1(b). Fora healthy stator insulation system, the leakage current is mostlycapacitive since the capacitive impedance is much smaller thanthe resistive impedance. The dissipation factor, DF, is definedas the tangent of the angle between IC and I, δ, as shown in(1), and the power factor (PF) is defined as the cosine of anglebetween I and IR , as shown in (2), where tilda, ∼, representsphasor quantities. For small angles of δ, DF, and PF are sim-ilar and used interchangeably in industry as an indication ofdielectric losses of insulating materials and systems

DF = tan δ = |IR |/|IC | (1)

PF = cos(90 − δ) = |IR |/|I|. (2)

There is much information that can be obtained from theDF measurements regarding the winding insulation conditionwhen the measurements obtained under the same test condi-tions are trended over time, and/or compared between phases.The DF test alone is an indication of inherent dielectric lossesand its general condition. The DF values increase with ther-mal deterioration and contamination and/or moisture absorp-tion [4], [5], [12]–[14]. The increase in the dielectric lossesdue to thermal deterioration can be explained microscopicallyas the tendency of thermal overload induced oxidation in-creasing the oscillation of the polar molecules [4]. Thermal


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LEE et al.: ONLINE TECHNIQUE FOR MONITORING INSULATION CONDITION OF AC MACHINE STATOR WINDINGS 739

Fig. 2. Proposed differential leakage current measurement technique for on-line assessment of stator winding insulation condition.

degradation of resin binders in groundwall insulation can alsocontribute to the creation of conductive or polar byproductscapable of increasing dielectric losses. Another explanation isthe increase in conduction current due to cracking or peelingof the insulation caused by thermal deterioration (with somecontamination). The dielectric losses also increase with partlyconductive contamination from foreign particles or moistureabsorption, since both the dielectric absorption and conductivelosses increase.

If the trends of both measurements C and DF are availableover time, insulation problems such as thermal degradation orcontamination/moisture absorption can be diagnosed with moreconfidence. If a trend of decrease in C, and increase in DF areobserved, this is a strong indication of thermal deterioration.If C and DF increase, this indicates insulation surface or bulkcontamination or moisture absorption. It should be noted that allthe measurements presented in this section provide indicationsof the average condition of a winding and not the condition ofthe most deteriorated area.

III. ONLINE INSULATION QUALITY MONITORING

A. Principles

The main concept for monitoring the stator insulation condi-tion online is to measure the leakage current flow through thestator insulation for each phase. This can be accomplished bymeasuring the differential current of the line and neutral end ofeach phase winding, as shown in Fig. 2. If the current sensorencloses both ends of the phase winding leads, only the cur-rent component leaking from the phase conductor through theinsulation to ground is measured, since the large main statorload current is canceled out. The leakage current of phase A,ia,l , shown in the figure consists of equivalent capacitive andresistive components, ia,C and ia,R , which will be shown inmore detail in Section III-B. By measuring the phase angle ofthe differential leakage currents with respect to the line-neutral(or ground) voltages, the values of DF and C can be calculatedonline based on (1) and Fig. 1. Trending the data from the con-tinuous online measurements of C and DF allows monitoring ofthe insulation condition while the machine is under operation.

Fig. 3. Typical terminal box configuration: differential CTs enclosing lineand neutral end of 3 phase stator windings for phase fault protection.

Fig. 4. Simplified on-line insulation model for a 3φ ac machine.

In a typical industrial setting for medium or high voltagemachines, the three neutral terminals are connected togetheroutside the machine in the terminal box, as shown in Figs. 2 and3. It is shown in Fig. 3 that the line and neutral ends of eachphase are accessible, and that a differential CT is placed in theterminal box to enclose both the line and neutral ends of eachphase. The CT does not measure the differential current withhigh precision since its purpose is to measure the large faultcurrents produced by phase faults.

B. Simplified Online Insulation System Model

Stator insulation systems are complex systems where thecomponents used for groundwall and phase to phase insulation,and its geometry, depends on the rated voltage and machinedesign. For the purpose of monitoring the overall insulation



Fig. 5. Per phase equivalent circuit for on-line and off-line differential leakagecurrent measurement in phase A.

condition online, a simplified insulation model shown in Fig. 4is considered, where nodes A, B, C, and G represent the statorwinding conductors of phase a, b, and c, and ground; and sub-scripts l, p, and g represent leakage, phase, and ground, respec-tively. The coupling between the phase and ground representsthe insulation that separates the copper conductors from thegrounded stator core (groundwall insulation), and the couplingbetween the phases represents the insulation that separates thecopper conductors between phases (phase to phase insulation).It is assumed that the coupling between the phases, pp, and phaseto ground, pg, are represented by an equivalent parallel capaci-tance and resistance [14], as in the single phase case shown inFig. 1(a). The equivalent capacitance and resistance parametersin Fig. 4 depend on the motor design and insulation materialsused for groundwall and phase to phase insulation systems. Inthis model, it is also assumed that the Zpg and Zpp are the samefor each phase (balanced insulation system).

The main differences between online and offline leakage cur-rent measurements are: 1) the voltage distribution across thestator conductor and 2) the influence of voltages in the adjacentphases on the phase to phase insulation system. When a DFtest is performed offline, the phase windings are separated atthe neutral end, and the two phases not under test are groundedto the stator core. When the phase under test is energized, aconstant voltage is applied evenly across the entire phase wind-ing. The voltage applied to the phase to phase insulation in thetwo adjacent phases is equal to the applied voltage. Using anexample of energizing phase A, it can be seen from Fig. 4 thatthe voltage across A–B, A–C, and A–G is equal to the appliedvoltage, Vapp, since B and C are grounded. The per-phase equiv-alent circuit for this offline test is shown in Fig. 5 (switch on).An analytic expression for the measured leakage current can bederived from Fig. 5 as (3), and the leakage current can also beexpressed in resistive and capacitive current components shownin (4) as follows:

Ia,l = Vapp · (1/Zpg + 2/Zpp) (3)

Ia,l = Ia,l,R + Ia,l,C

= Vapp

[(1

Rpg+

2Rpp

)+ jω(Cpg + 2Cpp)

]. (4)

When the machine is operating, the line end of the winding isat line-neutral voltage and the neutral end is at zero volts with

respect to ground assuming that the stator neutral is close to theground potential (balanced voltage operation). It can be assumedthat the line-neutral voltage is distributed linearly between theline end (Vln) and the neutral end (0) of the phase conduc-tors. Therefore, it can be assumed that the magnitude of theequivalent or average voltage between the A, B, or C phase con-ductors and ground is half the actual line-neutral voltage, shownin (5) as follows:

Vag,eq = Vag/2 Vbg,eq = Vbg/2 Vcg,eq = Vcg/2. (5)

In addition to the linear voltage distribution, the influence of theadjacent phases must also be taken into account when derivingan expression for the measured leakage current. The equivalentline voltages can be assumed to be approximately half the actualline voltages, shown in (6) as follows, if it is assumed that thevoltage distribution in all three phases is linear:

Vab,eq = Vab/2 Vbc,eq = Vbc/2 Vca,eq = Vca/2. (6)

From Fig. 4 and considering (5) and (6), it can be seen thatthe leakage current measured during motor operation is not thesame as (3). An analytic expression for the phase A leakagecurrent can be derived from the observations above as

Ia,l = Vag/(2 · Zpg) + (Vab + Vac)/(2 · Zpp) (7)

and the corresponding equivalent circuit is shown in Fig. 5. Theper-phase equivalent circuit can be further simplified as a circuitwith Req and Ceq in parallel assuming that the voltages of thethree phases are balanced. The measured leakage current foreach phase shown in (7) can be decoupled into resistive andcapacitive currents as

Ia,l = Ia,l,R + Ia,l,C

=

(Vag

2Rpg+

Vab + Vac

2Rpp

)

+ jω

(Vag

2Cpg +

(Vab + Vac)2

Cpp

)

=Vag

2

[(1

Rpg+

3Rpp

)+ jω(Cpg + 3Cpp)

]. (8)

The circuit shown in Fig. 1(a) can be used as the per phaseequivalent circuit for online measurement of the leakage current,where V is half of the line-neutral voltage of the phase wherethe differential current is measured, and the Req and Ceq areshown in (9) and (10) as follows:

Req = RpgRpp/(3Rpg + Rpp) (9)

Ceq = Cpg + 3Cpp. (10)

C. Stator Insulation Aging Mechanisms and Influenceon Online Measurement of Ceq and DF

When the motor is operating, the instantaneous values ofline to neutral voltage Vln and the leakage current Il can bemeasured for each phase, and processed to extract the phasorquantities—the magnitude and phase angle. From the phasors,the dissipation factor and equivalent capacitance of each phase



can be calculated as shown in (11) and (12), respectively, asfollows:

DF = tanδ = tan[90 − (Vln/Il)] × 100 (11)

Ceq = (2|Il | cos δ)/(ω|Vln|). (12)

The equivalent circuit parameters shown in Fig. 4 graduallychange with the insulation aging mechanisms such as thermaldeterioration, contamination, moisture absorption, or partial dis-charge activity, as described in Section II. It can be seen in (9)and (10) that the variations in both the groundwall and phaseto phase insulation quality are reflected in Req and Ceq; i.e.,Req is a function of both Rpg and Rpp and Ceq is a function ofboth Cpg and Cpp. Therefore DF and Ceq provide an indicationof the overall (average) insulation quality for each phase. Eachtype of insulation aging mechanism is reflected in the variationin the DF and Ceq measurements in a different way. Any type ofinsulation aging mechanism that increases the dielectric lossescauses a decrease in Req, and therefore an increase in DF. Thevalue of Ceq can either increase or decrease depending on thecondition. The following summarizes how each type of insula-tion aging mechanism is reflected in the variation in the DF andCeq measurements:

1) thermal deterioration—decrease in Ceq and increase inDF;

2) contamination—possible increase in Ceq and DF;3) moisture absorption—increase in Ceq and DF;4) partial discharge damage—increase in DF.The magnitude and degree of change in the DF and Ceq mea-

surements under the insulation degradation conditions listedabove depend heavily on the materials and design used for theinsulation system. Therefore, it is difficult to define an accep-tance criteria for the change in the values of DF and Ceq mea-surements. In addition, DF and Ceq measurements are sensitiveto the winding temperature, humidity, and the input voltagelevel; therefore, they must be taken into account when trendingthe measurements. The values of DF and Ceq must be trendedover time and between phases to obtain useful information re-garding the overall insulation quality. When performing offlineinsulation tests, it is critical to obtain the test data under thesame ambient temperature, humidity, and applied voltage level;otherwise the data must be adjusted to compensate for the dif-ferences in the conditions under which the data is obtained. Itshould be noted that the purpose of this paper is not to pro-vide information on data compensation for ambient conditionsor acceptance criteria for changes in DF and Ceq. The objectiveis evaluate the feasibility of measuring the DF and Ceq online,which has a potential for providing many benefits for monitor-ing the overall stator winding insulation quality, as summarizedin the following section.

D. Potential Benefits of Proposed Approach

The proposed approach is a noninvasive, low cost solution foronline insulation quality assessment that can be implemented onmost small to medium voltage machines. A high performancecurrent sensor can be installed to replace existing phase faultCTs in most cases. For cases where the three neutral terminals

are not accessible, the stator winding can be reconfigured to ac-commodate the current sensor. The data processing and trend-ing algorithms can be implemented into the motor monitoringsystem, which are installed in most modern industrial machineswhere reliability is important.

The main advantage of the proposed technique comes from itsonline insulation quality monitoring capability. Online monitor-ing does not require a costly outage for inspection, and providesthe measurements when the machine is exposed to actual oper-ating conditions. This is an important feature, since it is believedthat the fault revealing behavior for most faults in electric ma-chines can only be observed when it is operating.

In addition, online measurement of DF and Ceq can provide amore accurate assessment of the insulation condition. As men-tioned previously, a single offline test data for DF and Ceq hasno major diagnostic value unless it is trended over time. Whenperforming scheduled maintenance once every 3–6 years, theperiod for data comparison as a function of time is from oneshutdown to another, and the test must be performed carefullysince inconsistent data is meaningless, especially if the measure-ments are infrequent. For the proposed technique, measurementscan be obtained online under the entire ambient and operatingconditions of the machine. The data can be stored and trendedover a long period of time according to ambient conditions. Theamount of information available in the data is significant com-pared to the offline measurements; therefore, it is easier to trendthe data for a more precise assessment. With the trending basedon continuous measurements, the chances of predicting insu-lation failure are higher, and therefore, costly forced outagesdue to failure can be prevented. Another advantage of onlineassessment is the ability to prioritize and schedule maintenancefor the entire fleet of machines under consideration based onits present condition and predictions. This allows inspection tobe performed in a more efficient manner compared to regularperiodic inspections of machines, which can reduce the numberof costly outages. Establishing a database of the test data formachines of all ratings, vintage, and insulation types presentsa tremendous potential advantage towards advanced diagnos-tics capability for condition assessment, failure prediction, andprioritization and scheduling of maintenance.

The proposed technique can also be applied to all singlephase and three phase ac machines and transformers. It canalso be easily modified to accommodate any type of electricalequipment that has electrical insulation. In addition, the arcfaults caused by insulation degradation can also be predicted,which reduces the safety risks for the maintenance personnel.

IV. EXPERIMENTAL STUDY

A. Experimental Setup

To verify the feasibility of the proposed technique, tests wereperformed on a 480-V 20-A 15-hp induction motor with a ran-dom wound stator, where the three line and neutral terminalsare accessible. The three neutral terminals were connected out-side the motor, and a current sensor was installed to enclosethe line and neutral ends, as shown in the experimental setup inFig. 6. The line-neutral voltage was measured using a standard



Fig. 6. Experimental setup for testing the proposed method (15-hp motor).

Fig. 7. Equivalent circuit representation of experimental setup with variableresistor for simulating degradation of insulation condition.

600-V potential transformer, and a high performance activecurrent sensor was used to measure the differential leakage cur-rent with high resolution. For data acquisition, a commercial16-bit high speed digitizer was used for measuring Vag and Ia,l

at a sampling frequency of 20 kHz, at rated voltage and at noload. The data was low pass filtered with a cutoff frequency of4 kHz, and the discrete Fourier transform was used for extract-ing the magnitude and phase information from the instantaneousmeasurements at 60 Hz. A 0.5–80-MΩ external variable resistorRext was installed between the line end and ground of one phaseto simulate deterioration in the insulation condition due to higherlosses. The representation of the insulation equivalent circuit andthe test setup configuration that includes Rext is shown in Fig. 7.

B. Experimental Results

The first test performed was an offline test where the ratedvoltage is applied to the motor with the three neutral ends dis-connected from each other (floating). This applies a uniformbalanced three phase voltage across the conductors of the mo-tor, and there is no stator current flow (other than the leakagecurrent) since the path for the current is open-circuited. The cir-cuit representation is the same as in Fig. 7 with neutral terminalsdisconnected and ia equal to zero. This test allows measurementof the leakage current without the influence of the stator cur-rent. The equivalent circuit for this test is the same as the onedescribed in Section III-B for the online case except for the volt-age distribution. As can be seen in Fig. 7, the voltage of the lineand neutral ends with respect to ground is uniform at the rated

Fig. 8. Measurements of vag and ia ,l with neutral terminals disconnectedfrom each other and floating; stator load current, ia , is zero.

Fig. 9. Online measurement of vag and ia ,l at no load.

voltage. Therefore, the effective voltage applied to the insulationand the leakage current is two times larger than that of the on-line case. The measured waveform for vag and ia,l for the offlinetest are shown in Fig. 8, where the rms values of vag, ia,l andthe value of Ceq averaged over a 1 second interval are 289.9 V,696.9 µA, and 6.622 nF, respectively. The online measurementsof vag and ia,l for phase A are shown in Fig. 9, where the mea-sured rms values of vag, ia,l and the value of Ceq are 281.0 V,351.6 µA, and 6.633 nF, respectively. The rms value of ia,l isapproximately half of what was measured in the offline case,which verifies the assumptions made on the voltage distributionin Section III-B. It can be seen that the leakage current leadsthe voltage by almost 90, which indicates a capacitive current,as predicted. The calculated values of δ and DF are 2.34 and4.08%, respectively, for Fig. 9. The results shown in Figs. 8 and 9verify that the leakage current can be measured online using theproposed method. The calculated values of Ceq and DF can bemonitored continuously while the motor is operating to assessthe overall condition of the insulation system. The measure-ments for Ia,l , Ia,R , Ia,C , δ, DF, and Ceq for phases A, B, and Care summarized in Table I. It can be seen that the measurementsof DF for all three phases of the machine are high, and valuesof Ceq and DF between phases were significantly different thanexpected. It should be noted that the results obtained for the DFare completely different from the values obtained in offline tests



TABLE IMEASURED VALUES OF Ia ,l , Ia ,R , Ia, C, δ, DF, AND Ceq FOR

PHASES A, B, AND C ION OF Rext

due to different voltage distribution and influence of adjacentphase voltages. The DF values are higher since the result con-tains more information on the line end, which is more likely tobe damaged due to high stress. It is also suspected that the highvalues of the DF are due to the motor’s age (20+ years) and thefact that many tests were performed on the motor for inverterdrive development over many years. The differences of the Ceq

and DF values between phases can also be attributed to the factthat it is a random wound stator, where the insulation system isless likely to be balanced compared to form wound stators.

An external variable resistor, Rext, was connected betweenthe line end of phase A and ground to observe whether the pro-posed technique can detect ‘changes’ in the insulation condi-tion. The resulting per phase resistance of the insulation systemis Rext connected in parallel with Req. Therefore, a decrease inRext simulates any type of insulation problem that causes thedielectric losses (or DF) to increase in the insulation system dueto thermal degradation, moisture absorption/contamination, orpartial discharge damage. The value of Rext was adjusted from80 to 0.5 MΩ in discrete steps to obtain measurements of vag andia,l (80, 48, 32, 24, 16, 12, 8, 5, 2.5, 1, and 0.5 MΩ). It should benoted that IEEE 43 [12] recommends that the minimum value ofthe insulation resistance should be 5 MΩ for random wound sta-tors. The values of Rext were selected to check if the proposedmethod is capable of detecting incipient insulation degradationbefore failure occurs.

The instantaneous measurements of vag and ia,l over a 1-sduration were obtained and processed to calculate the values ofIa,l , Ia,R , Ia,C , δ,DF, Ceq for eleven different values of Rext,which is summarized in Table II. The waveforms of vag andia,l for when the values of Rext are 0.5, 1, 2.5, and 12 MΩ, andwhen Rext is open circuited, are shown in Fig. 10. It can be seenthat the magnitude of ia,l and δ increase as the value of Rext isdecreased. The values of Ia,l , I a,R , Ia,C , and δ, DF, Ceq shownin Table II are plotted for Rext = 1 ∼ 80 MΩ in Figs. 11 and 12,respectively. The data in Table II is also plotted in Fig. 13 inthe phasor diagram representation shown in Fig. 1(b). It shouldbe noted that the x and y axis scales in Fig. 13 are different fordisplay purposes; therefore, the δ angle is not the actual angle.From Table II and Figs. 11–13, a monotonic increase in Ia,R

and the δ angle (or DF) can be observed, as the value of Rext

is decreased. This indicates that the proposed technique can beused for assessing the condition of the insulation system accu-rately and help predict insulation failure with proper modelingand trending. The change in δ (or DF) can be clearly observedeven when there is an additional resistance path between theline end and ground as high as 80 MΩ. Considering that 5 MΩ

TABLE IIMEASURED VALUES OF Ia ,l , Ia ,R , Ia, C, δ, DF, AND Ceq

AS A FUNCTION OF Rext

Fig. 10. Waveforms of vag and ia ,l for Rext = 0.5, 1, 2.5, 12 MΩ.

Fig. 11. Measured values of Ia ,l , Ia ,R , Ia ,C forRext = 1 ∼ 80 MΩ.

is the recommended minimum value of insulation resistance,the proposed technique is capable of detecting incipient signsof insulation deterioration. Therefore, it is capable of providingthe user with very early indications of insulation failure.

It can also be observed in Table II and Fig. 11 that the mag-nitude of Ia,l increases as Rext is decreased; however, it doesnot provide a sensitive indication as the δ (or DF). A noticeablechange can only be observed when the value of Rext is decreased



Fig. 12. Measured values of δ, DF, and Ceq for Rext = 1 ∼ 80 MΩ.

Fig. 13. Phasor diagram representation of Ia ,C and Ia ,R as a function Rext.

to or below 2.5 MΩ. The differential current relays currently be-ing used for phase fault protection only monitors the magnitudeof the leakage current since the purpose of using phase faultrelays is to trip the machine after insulation failure occurs. Theresults shown in this work show that capability of predictinginsulation problems can be significantly improved by obtainingthe phase angle information in addition to the magnitude.

Table II and Figs. 11–13 also shows that the measured ca-pacitive current component and the Ceq estimates are constantand independent of the Rext value as expected, since it is onlythe resistive component of Ia,l that is being changed. It can beseen in Table II that the Ceq estimates are very consistent, whichshows the potential of monitoring Ceq and DF for assessment ofinsulation condition. It is difficult to simulate changes in the ca-pacitive component due to thermal degradation, contamination,or moisture absorption since it requires irreversible damage tothe test machine insulation. A procedure for testing machinesunder accelerated thermal degradation and/or moisture absorp-tion to observe the changes in Ceq and δ (or DF) is currentlyunder investigation.

V. RECOMMENDATIONS FOR FUTURE WORK

The scope of this work was to evaluate the feasibility ofmeasuring the leakage current for online measurement of DF

and Ceq. The experimental study presented in Section IV hasshown promising results for detecting insulation degradationin its early stages. However, there are practical issues to beresolved, and more work to be done regarding measurement ofIa,l , data processing, and interpretation. This section is dedi-cated to summarizing the practical issues regarding implemen-tation and recommendations for further work.

The first and most important step towards implementing theproposed technique is to obtain an accurate measurement of theleakage current. As stated in the preceding sections, the purposeof the conventional differential CTs used for phase fault protec-tion is to measure the magnitude reliably enough for protectionof the machine after the insulation failure occurs. Therefore, itcannot measure the magnitude and phase of the leakage cur-rent with high enough accuracy for implementing the proposedtechnique. Moreover, the measurements can be influenced by thecurrents in adjacent phases depending on the current level andcable arrangements in the terminal box. The differential CT usedfor the proposed technique must provide accurate magnitude andphase angle readings and shielded for EMI, if necessary. There-fore, the next steps of this work currently under considerationare CT design optimization and testing of larger machines toidentify the challenges of implementing the proposed idea.

The experimental study verified that the differential leak-age current can be measured for monitoring the capacitanceand dissipation factor online. Another important next step forthe implementation of the technique is to process the measure-ments to compensate for the influence of variations in operatingconditions such as stator insulation temperature, humidity, andvoltage level. Once this is established, algorithms for trendingthe processed measurements over time and between machinesand phases need to be developed. This will be a basis for in-terpretation for precise condition assessment and prediction ofinsulation failures for stator insulation systems. An extensivedatabase accumulated over a long period of time for a largenumber and types of machines under various operating condi-tions is critical for accomplishing this task.

VI. CONCLUSION

An online technique for monitoring the average insulationcondition of ac machine stator windings based on the measure-ment of the differential leakage current has been proposed inthis paper. An online stator insulation system model has alsobeen derived along with the basic guidelines for interpretationof the online measurements of Ceq and DF. An experimentalfeasibility study on a 15-hp induction machine has also beenpresented to verify the proposed idea.

The experimental results verified the validity of the onlineinsulation system model and showed that Ceq and DF can be es-timated consistently with high precision. It has also been shownthat degradation in the insulation system that results in decreasein Req can be detected with high sensitivity, which allows de-tection of incipient insulation degradation. The potential of theproposed technique on insulation condition assessment is signif-icant since it is a noninvasive and low cost solution that is capa-ble of monitoring the overall insulation condition continuously



while the machine is under operation. The information obtainedfor online condition assessment can also be used for prioritiz-ing and scheduling maintenance of the entire machine fleet, andtrended to help predict insulation failure. This allows inspectionto be performed in an efficient manner with reduced safety risksand chances of forced outages due to insulation failure.

ACKNOWLEDGMENT

The authors gratefully acknowledge C. Burnie, J. Hayward,D. Hanchar, and R. Bell for their assistance on the testing, andJ. Maughan for his support.

REFERENCES

[1] P. O’Donnell, “Report of large motor reliability survey of industrial andcommercial installations: Part I and II,” IEEE Trans. Ind. Appl., vol. 21,no. 4, pp. 853–872, 1985.

[2] P. F. Albrecht, J. C. Appiarius, and D. K. Sharma, “Assessment of re-liability of motors in utility applications-updated,” IEEE Trans. EnergyConvers., vol. 1, no. 1, pp. 39–46, 1986.

[3] “Monitoring und Diagnose elektrischer Maschinen und Antriebe,” AllianzSchadensstatistik an HS Motoren, 1996–1999, in VDE Workshop, 2001.

[4] G. C. Stone, E. A. Boulter, I. Culbert, and H. Dhirani, Electrical Insulationfor Rotating Machines, ser. IEEE Press Series on Power Engineering. NewYork: Wiley, 2004.

[5] I. Culbert, H. Dhirani, G. C. Stone, EPRI Power Plant Electrical ReferenceSeries in Handbook to Assess the Insulation Condition of Large RotatingMachines, vol. 16, 1989.

[6] A. J. Gonzalez, M. S. Baldwin, J. Stein, and N. E. Nilsson, Monitoring andDiagnosis of Turbine-Driven Generators. Englewood Cliffs, NJ: Prentice-Hall, 1995.

[7] G. C. Stone, “Advancements during the past quarter century in on-linemonitoring of motor and generator insulation monitoring,” IEEE Trans.Dielectr. Electr. Insul., vol. 9, no. 5, pp. 746–751, 2002.

[8] G. C. Stone, H. G. Sedding, and M. J. Costello, “Application of partialdischarge testing to motor and generator stator winding maintenance,”IEEE Trans. Ind. Appl., vol. 32, no. 2, pp. 459–464, 1996.

[9] D. M. Allan, M. S. Blundell, K. J. Boyd, and D. D. Hinde, “New insulationdiagnostic and monitoring techniques for in-service HV apparatus,” inInt. Conf. Properties and Applications Dielectric Materials, vol. 1, 1991,pp. 448–451.

[10] X. Huang, F. Bai, W. Gao, and Z. Yan, “A new on-line insulation diagnosticmethod for capacitive-type equipment,” in Proc. Power Syst. Technol.,vol. 1, 1998, pp. 100–104.

[11] P. Wang, M. R. Raghuveer, W. McDermid, and J. C. Bromley, “A digitaltechnique for the on-line measurement of dissipation factor and capaci-tance,” IEEE Trans. Dielectr. Electr. Insul., vol. 8, no. 2, pp. 228–232,Apr. 2001.

[12] Standard Test Methods for AC Loss Characteristics and Permittivity ofSolid Electrical Insulation, (2004).

[13] IEEE Recommended Practice for Measurement of Power Factor Tip-Upof Electric Machinery Stator Coil Insulation, (2000).

[14] IEEE Recommended Practice for Testing Insulation Resistance of Rotat-ing Machinery, (2000).

Sang Bin Lee (S’95–M’01) received the B.S. andM.S. degrees from Korea University, Seoul, Korea,in 1995 and 1997, respectively, and the Ph.D. degreefrom the Georgia Institute of Technology, Atlanta, in2001.

From 2001 to 2004, he was with the ElectricMachines and Drives Laboratory, General ElectricGlobal Research Center, Schenectady, NY, where hewas involved in research projects related to monitor-ing and diagnostics of electric machines. He is cur-rently a Professor of Electrical Engineering at Korea

University, Seoul, Korea. His research interests are in protection, monitoringand diagnostics, and control of electric machines.

Dr. Lee received the 2001 Second Prize Paper Award from the Electric Ma-chines Committee of IEEE IAS. He is a member of the IAS Electric MachinesCommittee.

Karim Younsi (M’91–SM’04) received the B.S. de-gree in electrotechnology from the University ofScience and Technology of Oran, Oran, Algeria, in1986 and the M.Sc. and Ph.D. degrees in electricalengineering-dielectric materials from Paul SabatierUniversity in Toulouse, France.

Most recently, he was an Insulation Systems Engi-neer with GE Power Systems, Schenectady, NY. Priorto that, he was an Insulation Research Engineer withGE Canada, City, ON, Canada, a Research Engineerwith Ontario Hydro in Toronto, and a Research Asso-

ciate with Queen’s University, City, ON, Canada. In 2003, he joined the ElectricMachines and Drives Laboratory, GE Global Research Center, Schenectady,NY, as a Dielectrics and Insulation Systems Engineer. He is currently involvedin the design and qualification of new insulation systems for electrical equip-ment such as medical systems, motors, and generators.

Dr. Younsi is a Registered Member of the Association of Professional Engi-neers of Ontario in Canada, and a member of the IEEE Dielectrics and ElectricalInsulation, Industry Applications, and Power Engineering Societies.

Gerald B. Kliman (S’52–M’55–SM’76–F’92–LF’95), deceased, received the S.B., S.M., and Sc.D.degrees from Massachusetts Institute of Technology,(MIT), Cambridge, in 1955, 1959, and 1965, respec-tively. He died in 2004.

From 2001 to 2004, he was a Research Professorin Electrical Engineering at the Rensselaer Polytech-nic Institute, after retiring from the General ElectricCompany. At GE Corporate Research and Develop-ment, he conducted fundamental studies of linear,synchronous, permanent magnet and induction mo-

tors, advanced drive systems for traction, the development of high-efficiencyand high-speed motors, electromagnetic pumps, and the application of new anddeveloping magnetic and nonmagnetic materials and insulations. A major em-phasis was the development of incipient fault detection techniques for electricmotors and drives. Following graduation from MIT he was an Assistant Profes-sor of Electrical Engineering at the Rensselaer Polytechnic Institute. Prior to GECorporate R&D, he had several assignments in GE’s Transportation SystemsDivision and Nuclear Energy Division where he worked on adjustable speeddrives, high-speed linear induction motors, large electromagnetic pumps, etc.He was also an Associate Editor of Electric Power Components and Systems.He has had 88 patents granted in his name and various publications includingseveral prize papers.

Dr. Kliman was a Senior Member of the American Institute of Physics.


an online technique for monitoring the insulation condition of ac machine stator windings

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