X射线探测焊缝及机械损伤方法概述----中英文翻译.docx

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1、Originaltext：X-RAYDETECTSWELDSANDMECHANICALSTRUCTUREDAMAGEMATHODS,SUMMARIZEThemovingsmallobjectdetectioninimageisalwaysadifficultprobleminfieldofimageprocessing,whichappliesinmanyfields,suchasindustrialdetectionandmedicaldetection.Thedefects,suchasblowholesandincompletepenetration,occasionallyappear

2、intheweldingprocess.Thesedefectscanaffectthequalityandthesecurityofproducts.Therefore,defectsdetectioninweldingseamisextremelyimportant.Now,theon-linedetectionofdefectsintheweldisstilldonebyhumaninterpreter.However,thisprocessissubjective,inconsistent,laborintensiveandfatigueofinterpreter.Itisdesira

3、bletofindaneffectiveautomaticdefectsdetectionmethodtoassisthumaninterpreterinevaluatingthequalityofweldandtomaketheon-linedetectionobjective,standardandintelligent.Ourresearchisbasedonthis.Wehavestudiedtheautomaticdefectsdetectionintheweldseamandmainlydonethefollowingresearch:(1)Thereismuchredundant

4、backgroundinformationforthedefectsdetectionintheimage.Thereforeweuseanautomaticallyabstractingmethodofweldareabasedontheauto-adaptedthresholdsegmentation.Thismethodcanreducethecomputationandincreasetheprecision.(2)TheSUSANalgorithmhasgoodanti-noiseability,whichcanrecognizetheimageedgeverywell.Soweha

5、vestudiedadefectsdetectionmethodbasedonSUSANalgorithm,whichassociatedwiththemorphologyoperation.Theresultsindicatethatthismethodiseffective.(3)Waveletanalysismethodhasaverygoodlocalizationcharacteristic,whichcanfocusonthearbitrarydetailoftheanalyzedobject.Therefore,Westudiedamethodusingwaveletdecomp

6、ositiontogettheshapeandpositioninformationofthedefects.Thenweusethewienerfilterandmorphologymethodtocompletethedetection.Theautomaticflawdetectionofweldedtubesisoneofthemostimportantstepstoensurethequalityofthetubes.Nondestructiveinspectiononweldingseamoftubeisrequiredinthetubeproduction,andrealtime

7、X-Rayradiographyinspectionisaneffectivemeans.Alongwithcontinuousimprovementoftheproductiveratio,thedemandfortheautomaticinspectiontotheweldingseambecomesmoreandmorepressing,soimplementationoftheautomaticinspectionpossessesimportantsignificanceonboththeoryandreality.Wavelettransformisapowerfultoolint

8、hesignalandimageprocessing,anditsfundamentaltheoryhasbeenformed.Fromtheviewofengineeringapplications,however,thewavelettransformisstillintheelementarystage,thefurtherResearchesarerequiredforthepracticaluses.Inthisthesis,Weconcentratemainlyonusingwaveletanalysisforweldingseamimageprocessingandrecogni

9、tion,andsomerelatedtechniquesaredeveloped.Forconstructingweldingseampositioninganddetectioncontrolsystem,themultiplecomputersconfigurationforweldseamimagerecognitionisproposed.ThesystemadoptsthearchitectureinwhichmultipleCPUsprocessparallelsunderthecontrolofthemasterIPCcomputer.Thesystemcanperformst

10、oringtheweldseamimages,positioning,flawsrecognizingandqualityprejudging.TheWatch-Doginterfacecardissuccessfullydeveloped;itcanimprovethesystemreliabilitybyredundanciestechniqueofsavingbreakpointdataandrestoringthem.ThehardwaresupportingthesystemmakesuseofthehighspeeddigitalsignalprocessorTMS320C30fr

11、omTaxaxInstrumentsCompany.Theframegrabbercancapture25framesofweldingseamimagepersecondcontinuouslyandmakeitpossibletofulfilltherealtimeweldingseamimageprocessingAndrecognition.TheonekindofimprovedFWT(FastWaveletTransform)algorithmforafinitesequenceisproposedafterstudyingtheoryofmustiersolutionanalys

12、isandanalyzingtechnicalcharacteristicsofDSP.TheimplementationoftheperiodicextensionoftheFWTonDSPisdescribedindetailandthecorrespondingFWTassemblycodeisdescribedfortheDSPTMS320C3Xseries.Thisdissertationsuggestsschemeofimagedemonizingbasedontwo-dimensionaldiscretewavelettransform.Thedemonizingalgorith

13、misdescribedwithsomeoperators.Bythresholdthewavelettransformcoefficients,ofnoisyimages,theoriginalimagecanbereconstructedcorrectly.Differentthresholdselectionsandthresholdmethodsarediscussed.Thenewrobustlocalthresholdschemeisproposed.Quantifyingtheperformanceofimagedemonizingschemesbyusingthemeansqu

14、areerror,theperformanceoftherobustlocalthresholdschemeisdemonstratedandiscomparedwiththeuniversalthresholdscheme.Theexperimentshowsthatimagedemonizingusingtherobustlocalthresholdperformsbetterthanthatusingtheuniversalthreshold.Inordertoimprovetheaccuracyandtherealtimeperformanceofedgedetection,ameth

15、odneedtobefoundtomatchthedetectionoflowcontrastblurredweldingseamimage.Thisdissertationanalyzedthemainsourcesofnoiseaswellasthedifferentcharacteristicsofnoiseandsignalunderwavelettransform,andproposedaMoultriesolutionedgedetectionmethodbasedonwavelettransform.Theexperimentalresultsshowtheeffectofthi

16、salgorithmisadvantageousoverthatoftraditionaledgedetectionalgorithm.Thegeometricalrelationofellipticimagingisstudiedforweldingseamimageofthebuttweldsinstraighttubes.Theregionmodelofweldingseamimageisproposed,Itfurnishesaevidencetheorytofurtherprocesstoweldingseamimage.Combiningwiththeregionmodel,amodel-basedadaptivetargetsegmentationalgorithmisproposed.OnebasisofthealgorithmisOtsu,sdiscriminatescriterion.Theadaptivetargetsegmentationofweldingseamimageisrealized.Theeffecto