简介：Weldshapecontrolisafundamentalissueinautomaticwelding.Inthispaper,adoublesidevisualsystemisestablishedforpulsedgasmetalarcwelding(P-GMAW),andbothtopsideandbacksideweldpoolimagescanbecapturedandstoredcontinuouslyinrealtime.Byanalyzingtheweldshaperegulationwiththemoltenmetalvolume,sometopsideweldpoolcharacterizedparameters(WPCPs)areproposedfordeterminingpenetrationinbuttweldingofthinmildsteel.Moreover,someBPnetworkmodelsareestablishedtopredictbacksideweldpoolwidthwithweldingparametersandWPCPsasinputs.
简介：Basedonthemethodofartificialneuralnetwork,anewapproachhasbeendevisedtopredictthemechanicalpropertyofE4303electrode.Theoutlinedpredicationmodelfordeterminingthemechanicalpropertyofelectrodewasbuiltupontheproductiondata.Theresearchleveragesabackpropagationalgorithmastheneuralnetwork'slearningrule.Theresultindicatesthattherearepositivecorrelationsbetweenthepredictedresultsandthepracticalproductiondata.Hence,usingtheneuralnetwork,predicationofelectrodepropertycanberealized.Forthefirsttime,thisresearchprovidesamorescientificmethodfordesigningelectrode.
简介：Laserblankweldingisbecomingmoreandmoreimportantintheautomotiveindustryandthequalityoftheweldiscriticalforasuccessfulapplication.Afullyautomatedsolutionisrequiredtoinspectthequalityoftheblanks.ThispaperpresentsavisioninspectionsystemwithaCMOScamerawhichusesART2networktoinspectthedefectson-linetoobtainthegeometryandthequalityoftheweldseam.TheneuralnetworkART2hasthecapabilityofself-learningfromtheenvironment.Itcandistinguishthedefectsthathavebeenlearnedbeforeandgivenewoutputsfornewdefects.SoART2networkissuitableforweldqualityinspectioninlaserblankwelding.Additionally,aCO_2laserisusedfortheblankbutt-welding.
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