Optimal Mising of Eddy Current Signals

8/12/2019 Optimal Mising of Eddy Current Signals

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DATA FUSION METHOD FORTHEOPTIMAL MIXINGOFMULTI FREQUENCY EDDY CURRENT SIGNALSZ. Liu,M.-S.Safizadeh,D . S. Forsyth, and B. A.Lepine

Structure,Material,an dPropulsion Laboratory, Institutefo rAerospace ResearchNationalResearch Council Canada, MontrealRd1191,Ottawa,ON K1AOR6,Canada

ABSTRACT. Eddy current testing methods arecommonly used in the inspection of aircraftfuselage splice joints fo r corrosion an d fatigue damage. However, th e inspection of thesecomponents suffers from th e spurious effects introduced by liftoff, interlayergaps, rivets, an dpaint. To overcome these effects, multi-frequency eddy current testingha sbeen proposed, buthas notbeen widely employeddue to the difficulty ofcorrectly mixing the different signals. Inthis study,weinvestigatedth epotentialofusingadatafusion techniquetocombineth eresultsofdifferentfrequenciesand quantifyhidden corrosioninservice-retiredaircraft lapsplice joints.A nupdating mechanism based on a contextual Dempster-Shafer approach wa s used to combineprobability mass values frommultiple sources.T he finalclassification results were obtainedb ymaking decisions basedon themaximum beliefof thefused results.

INTRODUCTIONManual eddy current ET) inspections are the most commonly used NDIprocedure in aircraft maintenance. Most often they ar ecalled for in the inspection ofcomponents fo rfatigue cracking,bu tthey have also shown potential fo rdetection an dquantificationof corrosiondamagein thefaying surfacesof fuselagesplicejoints.In

thecaseofsplicejoints,the ETsignalisaffected bychangesinthicknessof thejointmaterial, which is then assumed to be due to corrosion. The ET signal is alsoconfounded by a number of extraneous factors including variations in probe tilt,probe-specimen liftoff, an dinterlayergap tonameafew.Inordertoeliminate someoftheextraneous factors,themixingofmultiple frequenciesof ET hasbeen proposedbyvarious authors see for example [1,2]). However, these procedures have not beenadopted into common practice,atleastinpartdue to thecomplexityof theproceduresan dthesensitivityofanalog signal mixing .This paper presents resultsfrommultiplefrequency eddy current testing MFECT) whereth emixing isperformedbycomputerpost-test using datafusionalgorithms.When multiple inspections provide complementary information about thespecimen, combining the data may facilitate the analysis or classification process.Data fusion techniques provide a framework to fuse an d integrate information from

CP657,Reviewo fQuantitativeNondestructive Evaluation Vol 22 ,ed. by D. O.Thompsonand D. E.Chimenti2003 AmericanInstituteo fPhysics0-7354-0117-9577


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multiple sensors or sources. Dempster-Shafter (DS) theory is one of the data fusionapproaches that provide a mechanism to fuse information from multiple sources.Fusing of MFECT data is not a new topic and someresearchers presented variousfusion algorithmstoachieveabetter signal-to-noiseratio [3,4].The use of DSruletofuse nondestructive testing (NDT) data was described in reference [5] by Gros. Th eke y difference between DS andother common data fusion methodsis the assignmentof probabilitymass,which is the first and crucial step in the process. Unfortunately,there is no common answer to the question. This remains an unsolved problem andlargely dependson theapplicationitself.To detect an d characterize corrosion and fatigue damage in aging aircraft, inthecase of multi-layer rivetedjoints,the followingmetrics may be required: materialthicknesslossby laye r, corrosion pit size and d istribution, pillowing deformation; andcracksize,location,an dorientation [6,7].It is notlikelythatone single NDT methodcan characterize or quantify all these metrics. Because multiple NDT methods areemployed fo r these inspections, this raises th e potential fo r applying data fusiontechniques to interpret multi-sensor data or quantify th e results. At NRCC, thefollowing NDT methods are being used fo r detecting hidden corrosion in agingaircraft: single/multiple frequency eddy current, pulsed eddy current, ultrasonic, an dtwocomputervision based systems:Edgeo fLight andDSight inspection.

In this paper, we present the application of a DS fusion rule to fuse MFECTinspection data from Boeing 727 aircraft lap splice joints. A probability mass wasassigned to eachpixel,andafter applying the DS fusion rulea contextualprocessw ascarried out to update fused results. The decision was made based in the maximumbeliefof theupdated results.

APPLYINGDEMPSTER-SHAFERTHEORYThe DS Method

The core of the DS method contains three aspects: the concept of probabilitymass,belieffunction, and the updating mechanism[5,8].T heframe ofdiscernment 6is afinite set ofpropositions thata rem utuallyexclusive and exhaustive. Thepowerse tof 9 is 2,and theelementso fthisset are all subsets of9.The massfunction assignsdegree of beliefacrossthe set of all subsets of#,suchthat,

j n : 2*->[o , l ] , mfa)=0

The quantity m A), known as basic probability assignment (BPA), is a real numberbetween zero and one. It represents the exact beliefcommitted to A. A function Bel iscalledabelieffunction if itsatisfiesth e following conditions:

Jfe/:2'->[o,l], Belfa) = 0Bel A)=m B) ,forallAc9 2)

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Bel A) is a real number between zero and one that represents a degree of supportthat allthe available evidence provides for A. Given a belief function Bel A), the functionDbt A) = Bel -iA) is called a doubt function an d represents the total support for thenegationof aproposition.The plausibilityfunction of A, denotedby P1 A), is written asPl A) = l-Dbt A).

W eassume thecurrent stateof thesystemhas the value 7^(4) assigned to all thesubsets of 0 and represents the total support from all the previous evidence. Theobservation of a newdistinctpiece ofevidence by amassfunction m2, distributes a newset ofm ass values m2 Aj) over the set of29.These newmassvalue m2 and the oldvaluesm larecombinedtoproduce updated valuesmu.Th eupdatingmechanismi sperformedby :

3)

wheremu is called theorthogonalsum and can bewrittena smu =mlm2.Formula(3) iscalled the DS rule of combination. The crucial problem of using DS is how the massfunction distributes the mass values among the subsets of the frame of discernment.Unfortunately, DS theory does not give the answer. The procedure largelydependson theapplication.Th eProcedureo fPS basedContextualData Fusion

Th eprocedure thatw asusedfo rfusing MFECT datai sgiveninFigure 1.Torelatethe measurement value (voltage) to corrosion damage (material loss), one can use astraightforward calibration approach. That is , given a measured voltage, find the materiallosscorresponding tothatmeasurementusinga calibration curve. However, a m easuremen tvalue does not uniquely correspond to a material loss quantity, due to noise sourcesaffecting themeasured signal.Inthis work,it isassumed thattheactual materiallossfor ameasured value is normally distributed. While this has not been demonstrated for theMFECT data considered herein, this assumption has been widely used fo restimating theprobability ofdetection [9].This has also been demonstrated to hold true fordiverseN DEmethods[10]in amore general derivation.

ECT 5.5 kHz i

ECT 17IcHz

M :_M * -DataDistribution

.miM .,W2tW22

Fused ResultOS

RuleContextualProcessvm ax (A ).1,

massvalue ^ ^ ^ ^ MFIGURE 1. TheproceduretofuseMFECT data.

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One way toobtainthisdistribution is to use calibrationspecimens. Inorderfor theresults to accurately model the range of results expected from inspection of actual in-service components, all the relevant variables must be included in the calibrationspecimens.In thecase of riveted lap splice joints, these variables include paint,probe tiltan d liftoff, and interlayer gap variations. Construction of these calibration specimensquicklybecomes acomplex andarduous task. Thus, intheseexperiments, a sectionof anactual Boeing 727 lapsplicewasusedas prior knowledge tobuildthe distribution maps.The specimenw asinspected withthe MFECTtechnique describedbelow,an dthendestructively examined. After disassembly and cleaning, the individual layers werethickness mapped using a radiographic technique developed at NRCC. The range ofmeasured values of thickness was divided into 100 data bins, with each data bincorresponding to a modeled normal distributioncurve that satisfies formula (1). From thedistribution m ap, the probabilitymassvalue is assigned.Usually for DS methods the decision is made on the result of formula (3),but thecontextualinformation is not considered herein. Acontextual process integratesthe spatialcorrelation between adjacent pixels in order to improve the classification results [11]. Asimple implementation ofthisprocess computes the average o f a 3 by 3 block region:

M4)J=I >12(4,,, (4)yq=i-\r=j-lThe contextual process can be iterated if the procedure generates newly labeled pixels.Finally,each pixelis assigned to the type of corrosion with the maxim umbeliefvalue.

EXPERIMENTS ANDRESULTSA MIZ 40A eddy current instrument was used in the experiment to drive asliding probe h ousing withadjacentcoils in transmit/receive configuration. The probewa s excited at four discrete frequencies, -5.5 kHz, 8 kHz, 17kHz, and 30kHz,simultaneously during one scan. Th e Winspect data acquisition software wa s used

to capture theinspectiondata. The subjectspecimen was asectionof aservice-retiredBoeing 727 lapjoint.It consisted of two layersofnominal0.045 thickness A l2024-T3, and a stringer of Al7075-T6.The joint wasfastenedwiththreerivetrowsof equal1 spacing betweenrivets. Aphotographof thespecimenisshowninFigure2 and theinspection results ar e shown in Figure 3. After applying MFECT and other NDTinspections, the specimen was disassembled, cleaned, and the individual layersinspectedwitharadiographictechniquetodetermine remainingthickness.

FIGURE 2. Photographof a section of theBoeing727 lap splicejointusedfor this study.

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FIGURE 6.Th e difference between X-ray thicknessmap and fused resultsofsectionD 1stlayer (left)an d sectionC 1stlayer(right).

DISCUSSIONWhen pixel level data fusion is considered, an affine transformation thatregisters multi-sensor imagesshould beperformed inadvance(see,forexample [12]).Fortunately, fo rMFECT techniques, the discrete frequencies can be captured in onescan so the registration process can be omitted. However, to find the relationshipbetween the material loss and the voltage values ofMFECTmeasurement, there is still

theneedtomatchthe X-ray thicknessmapsan dMFECTimages.The problem isthatX-ray thickness map is of much higher resolution. Th e resizing of X-ray map to fi tMFECT images m ay introduce error and it would be better to perform a low-passfiltering before using it. Observing the material loss and MFECT measurement, wecannot find an y linear ornear linear relation between them asmightbe derived fromusing simple calibration specimens. This demonstrates that without dealing with theeffects of liftoff and interlayer gap, use ofcalibration data may not lead to acorrectevaluation result.In our experiments, we used the distribution map of section D as a prioriknowledge, and tested the resulting algorithm using section C. This works well forboth section C and D;however, if there are too fewpixels in certain data bins, thederived distribution curves may be inaccurate. This will affect the mass functionassignment especiallywhen the data to be evaluated hasmorepixelsinthisrange. Tosolvethisproblem, m oredatashould be collected tobuildthe distribution map.Th eresultsfor the first an dsecond layersareobtainedby fusing high and lowfrequency pairs respectively. It isobvious that fusion of the higher frequency imagesachievedabetter resultfor thefirst layer. Anycombinationof low andhighfrequencyimages doesno t improve the resultsfor evaluating first layer corrosion. This impliesthat data fusion does no t assure good results. When complementary information isavailable, an effective fusion operation will be helpful. Th e crucial step is the massfunction assignment. There arevarious approaches forthis and it largely depends onthe application itself. The mass function will be more reliable if a data-driven andobjectiveprocessis employed.

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CONCLUSION

In this paper, a data fusion scheme based on Dempster-Shafter theory ispresented fo r fusing multi-frequency eddy current data. The results of multiplefrequency eddy current inspections of hidden corrosion in a multilayer lapjoint ar equantified throughthisproposed approach. The results can then be used as the input tostructural analysismodels.Further improvement to the results will be attempted by obtaining more training datafromservice retiredspecimensinordertobettermodeltherelationshipbetween the eddy current signals and the thickness of the layers of thejoint. OtherNDI techniques could also be used, and results fused with th e MFECT results fo rimproved quantification andreliability.

ACKNOWLEDGEMENTSFunding of this work is provided by National Research Council Canada andDepartment ofNationalDefenceCanada, AVRS.

R F R N S

1. Thom pson, J.G., SecondLayer Corrosion DetectionUsingDualFrequencyEddyCurrentTechniques ,Presented at 1992 ATA NondestructiveTestingForum,Cincinnati,Ohio 25-27August 1992.2. Hagem aier, D.J.,Nguyen,K.,Materials Evaluation,52, No.l, 91 - 95(1994).3. Liu,Z ,Tsukada,K., Hanasaki,K. and Kurisu, M.,Research inNDE,11,165-177(1999).4. Yim,J. , ImageF usion Using Multiresolution D ecompositiona ndLMMSEFilter ,Ph.D. Thesis,Iowa StateUniversity,1995.5. Gros,X.E.,NDT DataFusion,Arnold,GreatBritain, 1997.6. Forsyth,D.S.and Kom orowski,J.P.,inSPIE Proceedings,Vol.3994, pp47-58(2000).7. Fahr,A .,Forsyth,D.S. andChapman, C.E., Surveyof N ondestructive E valuation(NDE) Tech niques for Corrosion in Aging Aircraft ,LTR-ST-2238,NRCC (26October 1999).8. Ham id, R., An Experimental Data Fusion Model forMultisensorSystems ,Ph.D.Thesis,NewMexicoStateUniversity, 1989.9. Alan P. B., NDE Reliability Data Analysis, Metals Handbook Volum e 17:Nondestructive Evaluationa ndQuality Control (9thed.),A SMInternational,659-701(1988).10. Forsyth, D.S., Fahr,A., inReviewof Progress inQNDE, Vol.19B,eds.D. O.Thompsonand D . E. Chim enti, Plenum, New York, pp2159-2166 (2000).11. Solaiman,B.,Pierce,L.E.and Ulaby,F.T.,IEEE Tran. Geos.Remo. Sens.3 7,No.3,ppl316-1326(1999).12. Liu,Z.,Forsyth,D.S.,Reg istrationof M ulti-modal NDIImagesforAgingAircraft,To bepublishedinResearch inNDE.

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Optimal Mising of Eddy Current Signals