简介：Weldpoolcontainssignificantinformationabouttheweldingprocess.TheweldpoolimagesofMAGweldingaredetectedbyLaserStrobesystem.AnalgorithmforextractingweldpooledgeisproposedaccordingtothecharacteristicsofMAGweldpoolimages.Themaximumweldpoollengthandwidtharecalculated.ThemeasurementdatacanbeusedtoverifytheresultsofweldingprocesssimulationandtoprovideagoodfoundationforautomaticcontrolofMAGweldingprocess.

简介：Imagesensorhasbeenoneofthekeytechnologiesinintellectualizedroboticswelding.Edgedetectionplaysanimportantrolewhenthevisiontechnologyisappliedinintellectualizedweldingroboticstechnologies.Thereareallkindsofnoisesinweldingenvironment.Thealgorithmsincommonusecannotbeappliedtotherecognitionofweldingenvironmentdirectly.Theedgeofimagescanbefellintofourtypes.Theweldimagesareclassifiedbythecharacteristicofweldingenvironmentinthispaper.Thispaperanalyzessomealgorithmsofedgedetectionaccordingtothecharacterofweldingimage,somerelativeadvantagesanddisadvantagesarepointedoutwhenthesealgorithmsareusedinthisfield,andsomesuggestionsaregiven.Thefeatureextractionofweldseamandweldpoolaretwotypicalproblemsintherealizationofintellectualizedwelding.Theiredgefeaturesareextractedandtheresultsshowtheapplicabilityofdifferentedgedetectors.Thetradeoffbetweenprecisionandcalculatedtimeisalsoconsideredfordifferentapplication.

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简介：ThelateralwaveinultrasonicTOFD(timeofflightdiffraction)imagehasatailintransittime,whichdisturbsthedetectionandevaluationofshallowwelddefect.Meanwhile,thelateralwaveandback-wallechothatactasbackgroundaddredundantdataindigitalimageprocessing.Inordertoseparatedefectwavefromlateralwaveandpreparethewayforfollowingimageprocessing,analgorithmofbackgroundremovalmethodnamedasmean-subtractionisdeveloped.Basedonthis,animprovedmethodbystatisticoftheenergydistributionintheimageisproposed.Theresultsshowthatbychoosingproperthresholdvalueaccordingtotheaxialenergydistributionoftheimage,thebackgroundcanberemovedautomaticallyandthedefectsectionbecomespredominant.Meanwhile,diffractivewaveofshallowwelddefectcanbeseparatedfromlateralwaveeffectively.

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简介：Duetothedisturbancesofspatters,dustsandstrongarclight,itisdifficulttodetectthemoltenpooledgeandtheweldlinelocationinCO2weldingprocesses.Themedianfilteringandself-multiplicationwasemployedtopreprocesstheimageoftheCO2weldinginordertodetecteffectivelytheedgeofmoltenpoolandthelocationofweldline.TheB-splinewaveletalgorithmhasbeeninvestigated,theinfluenceofdifferentscalesandthresholdsontheresultsoftheedgedetectionhavebeencomparedandanalyzed.TheexperimentalresultsshowthatbetterperformancetoextracttheedgeofthemoltenpoolandthelocationofweldlinecanbeobtainedbyusingtheB-splinewavelettransform.Theproposededgedetectionapproachcanbefurtherappliedtothecontrolofmoltendepthandtheseamtracking.

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