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dc.contributor.authorMartín, Óscar
dc.contributor.authorAhedo García, Virginia 
dc.contributor.authorSantos Martín, José Ignacio 
dc.contributor.authorGalán Ordax, José Manuel 
dc.date.accessioned2022-02-02T10:20:06Z
dc.date.available2022-02-02T10:20:06Z
dc.date.issued2022-01
dc.identifier.urihttp://hdl.handle.net/10259/6386
dc.description.abstractResistance spot welding (RSW) is a widespread manufacturing process in the automotive industry. There are different approaches for assessing the quality level of RSW joints. Multi-input-single-output methods, which take as inputs either the intrinsic parameters of the welding process or ultrasonic nondestructive testing variables, are commonly used. This work demonstrates that the combined use of both types of inputs can significantly improve the already competitive approach based exclusively on ultrasonic analyses. The use of stacking of tree ensemble models as classifiers dominates the classification results in terms of accuracy, F-measure and area under the receiver operating characteristic curve metrics. Through variable importance analyses, the results show that although the welding process parameters are less relevant than the ultrasonic testing variables, some of the former provide marginal information not fully captured by the latter.en
dc.description.sponsorshipThis work was supported in part by the Spanish Ministry of Science, Innovation and Universities (Excellence Networks) under Grant HAR2017-90883-REDC and Grant RED2018-102518-T, and in part by the Junta de Castilla y León Consejería de Educación under Grant BDNS 425389. The work of Virginia Ahedo was supported by the European Social Fund.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.ispartofIEEE Access. 2022, V. 10, p. 6518-6527en
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectResistance spot weldingen
dc.subjectQuality controlen
dc.subjectWelding parametersen
dc.subjectUltrasonic testingen
dc.subjectTree ensemblesen
dc.subjectStackingen
dc.subjectWeldingen
dc.subjectAcousticsen
dc.subjectClassification algorithmsen
dc.subjectElectrodesen
dc.subjectSteelen
dc.subjectBoostingen
dc.subjectTestingen
dc.subject.otherMaterialeses
dc.subject.otherMaterialsen
dc.subject.otherIngeniería mecánicaes
dc.subject.otherMechanical engineeringen
dc.subject.otherEnsayos (Tecnología)es
dc.subject.otherTestingen
dc.titleComparative study of classification algorithms for quality assessment of resistance spot welding joints from preand post-welding inputsen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1109/ACCESS.2022.3142515es
dc.identifier.doi10.1109/ACCESS.2022.3142515
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/HAR2017-90883-REDC/ES/Simular el pasado para entender el comportamiento humanoes
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RED2018-102518-T/ES/SISTEMAS COMPLEJOS SOCIOTECNOLOGICOSes
dc.identifier.essn2169-3536
dc.journal.titleIEEE Accessen
dc.page.initial1es
dc.page.final1es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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