Detection of Stator Winding Inter-Turn Short Circuit Faults in Permanent Magnet Synchronous Motors and Automatic Classification of Fault Severity via a Pattern Recognition System

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dc.authoridGumus, Bilal/0000-0003-4665-5339
dc.authoridArkan, Muslum/0000-0001-5313-2400
dc.authorwosidGumus, Bilal/S-6296-2016
dc.authorwosidÇIRA, Ferhat/AAA-5039-2021
dc.authorwosidArkan, Muslum/A-5114-2016
dc.contributor.authorCira, Ferhat
dc.contributor.authorArkan, Muslum
dc.contributor.authorGumus, Bilal
dc.date.accessioned2024-08-04T20:57:36Z
dc.date.available2024-08-04T20:57:36Z
dc.date.issued2016
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIn this study, automatic detection of stator winding inter-turn short circuit fault (SWISCFs) in surface-mounted permanent magnet synchronous motors (SPMSMs) and automatic classification of fault severity via a pattern recognition system (PRS) are presented. In the case of a stator short circuit fault, performance losses become an important issue for SPMSMs. To detect stator winding short circuit faults automatically and to estimate the severity of the fault, an artificial neural network (ANN)-based PRS was used. It was found that the amplitude of the third harmonic of the current was the most distinctive characteristic for detecting the short circuit fault ratio of the SPMSM. To validate the proposed method, both simulation results and experimental results are presented.en_US
dc.description.sponsorshipScientific Research Unit (SRU), Inonu University [2013/57]en_US
dc.description.sponsorshipThis work was supported by Scientific Research Unit (SRU), Inonu University, Project No: 2013/57.en_US
dc.identifier.doi10.5370/JEET.201.6.11.2.416
dc.identifier.endpage424en_US
dc.identifier.issn1975-0102
dc.identifier.issn2093-7423
dc.identifier.issue2en_US
dc.identifier.startpage416en_US
dc.identifier.urihttps://doi.org/10.5370/JEET.201.6.11.2.416
dc.identifier.urihttps://hdl.handle.net/11616/102775
dc.identifier.volume11en_US
dc.identifier.wosWOS:000370909800017en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherSpringer Singapore Pte Ltden_US
dc.relation.ispartofJournal of Electrical Engineering & Technologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCondition monitoringen_US
dc.subjectDigital signal processingen_US
dc.subjectFault detectionen_US
dc.subjectFault severity classificationen_US
dc.subjectPattern recognition systemen_US
dc.subjectPermanent magnet synchronous motorsen_US
dc.titleDetection of Stator Winding Inter-Turn Short Circuit Faults in Permanent Magnet Synchronous Motors and Automatic Classification of Fault Severity via a Pattern Recognition Systemen_US
dc.typeArticleen_US

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