structural health monitoring - uta.edu talks/lewis talk shm 09.pdf · structural health monitoring...
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Automation & Robotics Research Institute (ARRI)The University of Texas at Arlington
F.L. Lewis, Fellow IEEE, Fellow IFAC, Fellow UK InstMCMoncrief-ODonnell Endowed Chair
Head, Controls & Sensors Group
http://ARRI.uta.edu/[email protected]
Structural Health Monitoring
Rytters Levels:
Worden et al. 2009
Machine Learning
Methods of Learningsupervisedunsupervisedreinforcement
classification
SHM
defect
Interrogate (active or passive)
Change in propertyMaterialSample
sensors
Property Changes:visualacoustictemperature, pressurethermal conductance propertiesmagnetic propsglobal props.- Modal- stiffness, vibration freqslocal props local vibration freqs, impedance
strain, stressforce causes AE stress waves
wave propagation properties scattered, reflected, freq content
Model-basedData-based DSP
filter, preprocess, detrendFeature extraction
Decision-makingBayesNNfuzzyrule-based
Diagnosis & PrognosisDetectionClassificationLocalizationAssessmentPrediction
Fault Types
CompositesMatrix (resin) crackDelaminationFibre breaks
MetalsMaterial Defects
CorrosionCrackFatigue
System Defects Rivet FailureSurface Ice
Detection Methods
Vibration (LF- wavelength >> plate thickness)global- LF - changes in structural props- stiffness, vibr. freqs. local- HF changes in res. freqs., impedance
SonicUltrasound (HF- wavelength
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Electromagnetic spectrumhttp://imagers.gsfc.nasa.gov/ems/waves3.html
Sound
Frequency in Hz
Wavelength (STP at sea level)
20 200 2,000 20,000
Infrasound Ultrasound
Humans DogsElephants
100,000
Cats
BatsDolphins
200,0005
50m 10m 1m 10cm 1cm 1mm
Sound
Frequency in Hz
Wavelength (STP at sea level)
20 200 2,000 20,000
Infrasound Ultrasound
Humans DogsElephants
100,000
Cats
BatsDolphins
200,0005
50m 10m 1m 10cm 1cm 1mm
Acoustic Spectrum
Sensor Modalities
Overlap in freqs!
Transmission depends on the medium
Sensors Based on Physical Transduction Principles
Mechanical SensorsPiezoresistive Effect converts an applied strain to a change in resistance Piezoelectric Effect converts an applied stress (force) to a potential difference. PZTCapacitive Sensors convert displacement (force) into change in capacitance
Magnetic and Electromagnetic Sensors do not require direct physical contactHall Effect. Magnetic field applied perpendicular to current flow causes induced voltageMagnetic Field Sensors detect metallic objectsEddy Current Sensors use magnetic probe coils to detect defects in metallic structures
F.L. Lewis, Wireless Sensor Networks, in Smart Environments: Technologies, Protocols, Applications, Chapter 2, ed. D.J. Cook and S.K. Das, Wiley, New York, 2005.
Thermal Sensors measure temperature or heat fluxThermo-Mechanical Transduction. Heat causes thermal expansionThermoresistive Effects. Resistance R changes with temperature TThermocouples. Junctions of two different metals at different temperatures causes current flowResonant Temperature Sensors. Temp change in some materials causes a change in resonant frequency
Optical Transducers. Convert various properties to lightOptical fiber interferometers and gratings changes in length (strain), temp. cause changes in phaseOptical fiber accelerometers based on time of flight
Acoustic SensorsUltrasound. High Frequency. Can penetrate structures. Reflected and scattered from defectsAcoustic Wave Sensors
surface acoustic wave (SAW), thickness-shear mode (TSM), flexural plate wave (FPW), or acoustic plate mode (APM)
PiezoelectricSensor- develops a voltage difference across two of its faces when compressed Actuator- physically changes shape when an external electric field is applied
PyroelectricHeat Sensor- Develops a voltage difference across two of its faces when it experiences a temperature change.
TEMP. COMPENSATION
Ferroelectric-Has a spontaneous electric polarization (electric dipole) which can be reversed in the presence of an electric field.
PZT - Lead zirconate titanate
X-rayVisualCoherent OpticsFiber optics no EMI, lightweight, low noise, high BW
InterferometryFiber Bragg Grating - FBG
Thermography - IRMagnetics
Eddy currenta coil induces eddy currents in a conductive sampledefects cause change in the impedance of the sample
Interrogation / Interaction Modalities
Group 1
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Ultrasound HF (5 MHz)wavelength > thickness
Group 4- Strain, Stress
Force on defect causes AE stress waves
wikipediaLamb Waves
Elastic waves that propagate in a solid thin plate
2-D Wave equation
solutions split into two sets of waves-symmetric & antisymmetric
Irradiate entire thicknessPropagate substantial distances
S0 Extensional mode
A0 Flexural mode
wavelength ~ thickness
s0 Scattered and reflected by crack
a0 Detects delamination
A major challenge and skill in the use of Lamb waves for ultrasonic testing is the generation of specific modes at specific frequencies that will propagate well and give clean return "echoes". This requires careful control of the excitation and identification of the correct waves.
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Eddy-coil EM actuatordischarges capacitor through a coil, induces pulsed magnetic field in conductive sample,generates a forceneeds 1-10 J
Passive vibration monitoring-in-flight aircraft vibration freqs are very lowsuccessful in a boat hull monitoring application
Actuation / Interrogation
Active vs. Passive
PZT actuator
Active -
Actuator interrogation signalsBurst sinusoids
kk-N
has DFT
Square window DFT swamps out the signal DFT
time freq
Square window
Hamming window
Hann window
FFT of burst sinusoids with: time freq
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Chaotic Interrogator Actuation Todd et al. 2009
Actuation by Lorenz Signal
Signals received atsensors
Sensor 1 Sensor 2
Actuator and Sensor Locations
Based on Physical ModelsFEA or dynamics model
Based on Engineering KnowledgeTodd et al. 2009FBG sensors on Boat waterjet
Worden & Manson 2009CR = actuatorCi= PZT sensors
3 sensor networks based onknown damage regions
Ihn & Chang 2004Sensors along a rivet joint andBuilt into a composite skin
c.f. human nervous system proprioceptors
Deploy at Hot SpotsDeploy over a Large Area-
limits the frequencies and interrogation methods
No methodical procedures
Aircraft wing
Features
Time momentsFrequency domain properties-
Resonant freqs, sidebandsPower content in specific frequency bandsTransmissibilities
Strain, stress
Transmissibility from sensor j to sensor i
( )( )( )
iij
j
PSDTPSD
=
Do DFT for sensor i signal
actuatorSensor i
Do DFT for sensor j signal
Sensor j
( )ijT
Time-Varying Frequency ContentShort Time Fourier Transform Windowed DFT
time
frequency
Must select window lengthMust use good window w(n) - Hamming, Hann
WaveletDoes not need windowMulti-resolution analysis
Hilbert-Huang Transform (HHT)
2 ( 1)( 1)/
( 1)( , ) ( ) ( )
tj k n N
n t NX k t x n w t n e
=
= STFTSpectrogram
Wavelet xformScaleogram
Basic or mother wavelettime
freq
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Fault detection & Identification
Model-Basedmake physical model using FEA or physics-based methodsdetermine comparison metriclook for departures of real measured data from the model
Data-Basedbased on moments, freq response, or statisticsestablish normal operating limits basedestablish abnormality thresholdsdepartures indicate faults
Both methods look for departures from the normthis means Statistical Pattern Recognitionpreprocessing of data, filter, detrendoutlier rejection
Variations of available empirical and deterministic fatigue crack propagation models are based on Paris formula:
Where: = instantaneous length of dominant crack = running cyclesCo, n = material dependent constants = range of stress intensity factor over one loading cycle
( )no KCdNda
=
e.g. Deterministic Crack Propagation Modelse.g. Deterministic Crack Propagation Models
Physical Modeling
Dr. George Vachtsevanoshttp://icsl.gatech.edu/icsl
Ihn and Chang 2004
Lamb Waves
Must focus on ONE frequency
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Nascent freq
Where is the right Lamb wave?
Use s0 for cracksUse a0 for composite delamination
Group velocity Dispersion
From FEA for the specific material G
roup
vel
ocity
Frequency
s0 arrives before a0 below 600kHz
Time
Freq
uenc
y
s0 a0
Optimal sensor location wrt crack
Ihn and Chang 2004Smart Suitcase
Acellent Technol. Smart patch
Rivet failure
Cracks0
Debonda0
Composite faults
Acellent Smart Layer
a0
s0
debond
crack
Dam
age
inde
xD
amag
e in
dex
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Tomography- imaging by sections using wave energy2D or 3D images
x-ray CTgammaelectron
Reconstruction algorithmsfiltered back projectioniterative reconstruction
ART- algebraic reconstruction techniques(Kaczmarcz algorithm)
wikipediaCardiac CT scan
s0 energy- compute energy up to MAXIMUM PeakUse RMS value for tomographic reconstruction
Sticky gum to hold sensors?
Split plate into a uniform gridMount sensors at grid points400 sensors!
Freq = 500 kHz
Uniform angular sampling of plate with few sensors
Improved sensor placement
Wide band Lamb wavesExcitation rectangular impulse 10 microsec wideExcites Lamb waves covering a broad frequency spectrum
Used Kohonen NN to classify damage
Compensate for Propagation- amplitude A with distance x
Hickman et al. 1991
LF vibration 1-5 kHz
Defects cause energy redistribution in freq. spectrogram
FEA
Rivet removal and cracks both lower the HF content
Select Features?
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24 sq. plate, 0.08 thick
Eddy coilActuator1-10 J
Screwsaroundedges
Sensor placement determined experimentally!
Compute features for each sensor
Best Features:Energy distribution- Power in specific freq bands
3-4PZT sensors
NN classification?
Features-Energy distribution- Power in specific freq bands
1-1.5 kHz
1.5-3 kHz
Rivet failuresCracksicing
Power in freq range 1-1.5 kHz
Pow
er in
freq
rang
e 1.
5-3
kHz
Aircraft Monitoring Wing cuff
1. Damage detection
EDS
EDS= Electrodynamic shakerLF EM Vibration at 1-2 kHzCompute DFT
4 PZT sensors
Transmissibility from sensor j to sensor i
( )( )( )
iij
j
PSDTPSD
=
1 2
3
4
panel
Damaged panels
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Features = power in specific freq bands
Classification and departure detectionNNclustering (K-means, NN)outlier analysis using norm distance measure
Training data Set and Validation Set
Unsupervised learning for fault detection
Band 1 Band 2
No fault
crack
2. Damage Location
Network of sensors
Damage = remove panels
CR = PZT actuatorCi = PZT sensors
NN MLP classifier competitive learning
Supervised learning for fault classification or fault location
Actuator and sensor locations based onKNOWN possible fault locations
4 networks with 1 actuator and 3 sensors
Fiber Bragg Grating FBG
Interrogate length scales in the mm rangeNo EMILightweightCan be directly photo written into silica fiber using UVEmbed inside composites
2r nT =n= fiber core model index, T= grating period
Axial compression or tension changes T can measure strain
Boat Hull Monitoring passive wave excitationJoint Degradation active excitation - EDS
about 0.1-0.3 nm
A-K= 11 sensor arrays56 sensors in allRosette= 3-D sensor?
Boat Hull Monitoring
Passive excitation
Sensor placementhull monitoringwaterjet monitoring
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Discrete wavelet transformSet scale factor equal to 2j
Feature selectionSelect specific levels only
No defect
Defect
1024
516256
128
1996 IEEE Ultrasonics Symp.
Changes in time delay and freq due to physical quantity y(t)
Interrogation freqs 434MHz = 5-10 m RFID range2.5 GHz = 1-2 m RFID range
SAW + RFID
Gate this part = 1-2 micro sec
Sensitive to y(t) = temp., displacementy(t)= strain, force, accel. needs proper packaging
Haiying Huang, ME Dept, UTA
Passive induction coupling-remote interrogation
Res f
req f 01
Res freq f10
Strain causesRes freq shift
Patch Antenna
Crack Monitoring Haiying Huang, ME Dept, UTA
Res f
req f 01
Res freq f10