Publication:
Determination of optimum operation cases in electric arc welding machine using neural network

dc.contributor.authorGÖKMEN, GÖKHAN
dc.contributor.authorsAkinci, Tahir Cetin; Nogay, Hidir Selcuk; Gokmen, Gokhan
dc.date.accessioned2022-03-14T08:21:03Z
dc.date.accessioned2026-01-11T10:38:07Z
dc.date.available2022-03-14T08:21:03Z
dc.date.issued2011-04
dc.description.abstractWith arc welding machines, welding is only performed at optimum operating points. Determination of optimum operating points is important so as for welding machines which will be produced in future to be developed in a manner to operate in such parts. In this study, an Artificial Neutral Networks method was used in order to determine the optimum operating points of Electric Arc welding machine. For this purpose, a measurement system used to get the current measurements during the welding operation. A welding process includes some stages like initial case; transient case and operation case respectively. So as to use ANN model, a data set was established via time series. ANN is trained with 90% of data set and tested with 10% thereof At the end of the test, a prediction of 97.49% was made according to the regression value. And according to the MSE value, it was understood that a successful prediction was made with an error of 0.00353075 values.
dc.identifier.doi10.1007/s12206-011-0202-9
dc.identifier.eissn1976-3824
dc.identifier.issn1738-494X
dc.identifier.urihttps://hdl.handle.net/11424/241603
dc.identifier.wosWOS:000289534400021
dc.language.isoeng
dc.publisherKOREAN SOC MECHANICAL ENGINEERS
dc.relation.ispartofJOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectElectrical arc welding machine
dc.subjectOptimum operation cases
dc.subjectTime series
dc.subjectWelding analysis
dc.titleDetermination of optimum operation cases in electric arc welding machine using neural network
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage1010
oaire.citation.issue4
oaire.citation.startPage1003
oaire.citation.titleJOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
oaire.citation.volume25

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