Rotor Bar Fault Diagnosis by Using Power Factor

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dc.contributor.authorArabaci, Hayri
dc.contributor.authorBilgin, Osman
dc.contributor.authorUrkmez, Abdullah
dc.date.accessioned2020-03-26T18:16:00Z
dc.date.available2020-03-26T18:16:00Z
dc.date.issued2011
dc.departmentSelçuk Üniversitesien_US
dc.descriptionWorld Congress on Engineering (WCE 2011) -- JUL 06-08, 2011 -- Imperial Coll, London, UNITED KINGDOMen_US
dc.description.abstractThe paper presents detection and classification of rotor bar faults at steady state operation in squirrel cage induction motor by using power factor. One phase current and voltage of the stator coils were used to calculate the power factor. To investigate effects of rotor faults on the power factor, its frequency spectrum was obtained by fast Fourier Transform (FFT). Significant picks in the spectrum were used to discern "healthy" and "faulty" motor conditions. The motor conditions were classified by Artificial Neural Network (ANN). In experiments three different rotor faults and healthy motor conditions were investigated by 30 HP, 8", with 18 bars, 380V, 2 poles and 50 Hz squirrel cage submersible induction motor. The proposed decision structure detects and classifies rotor bar faults with 100% accuracy.en_US
dc.description.sponsorshipInt Assoc Engineers, IAENG, Soc Artificial Intelligence, IAENG, Soc Bioinformat, IAENG, Soc Computer Sci, IAENG, Soc Data Min, IAENG, Soc Elect Engn, IAENG, Soc Imagl Engn, IAENG, Soc Ind Engn, IAENG, Soc Informat Syst Engn, IAENG, Soc Internet Comput & Web Serv, IAENG, Soc Mech Engn, IAENG, Soc Operat Res, IAENG, Soc Sci Comput, IAENG, Soc Software Engn, IAENG, Soc Wireless Engnen_US
dc.description.sponsorshipScientific Research Project of Selcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThe study has been supported by Scientific Research Project of Selcuk University.en_US
dc.identifier.endpage984en_US
dc.identifier.isbn978-988-19251-4-5
dc.identifier.issn2078-0958en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage981en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/26792
dc.identifier.wosWOS:000393012800012en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherINT ASSOC ENGINEERS-IAENGen_US
dc.relation.ispartofWORLD CONGRESS ON ENGINEERING, WCE 2011, VOL IIen_US
dc.relation.ispartofseriesLecture Notes in Engineering and Computer Science
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectBroken rotor baren_US
dc.subjectfault diagnosisen_US
dc.subjectinduction motorsen_US
dc.subjectFast Fourier Transformen_US
dc.subjectArtificial Neural Networken_US
dc.titleRotor Bar Fault Diagnosis by Using Power Factoren_US
dc.typeConference Objecten_US

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