The detection of rotor faults by using Short Time Fourier Transform

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dc.contributor.authorArabaci, Hayri
dc.contributor.authorBilgin, Osman
dc.date.accessioned2020-03-26T17:18:24Z
dc.date.available2020-03-26T17:18:24Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.descriptionIEEE 15th Signal Processing and Communications Applications Conference -- JUN 11-13, 2007 -- Eskisehir, TURKEYen_US
dc.description.abstractIn this paper an experimental study detecting of rotor faults in three-phase squirrel cage induction motors by means of Short Time Fourier Transform (STFT) is presented. The frequency spectrum of motor line current is exploited for the detection. By obtaining a number of frequency spectrums from a current data with STET and averaging these spectrums, faults are diagnosed instead of Fast Fourier Transform frequently applied at the detection of broken rotor faults in the literature. Five different faulted rotors are investigated. These faults are one bar with high resistance of the rotor, one broken bar of the rotor, two broken bars of the rotor, three broken bar of the rotor and broken end ring of the rotor. Artificial Neural Network is used for classification of faults. Test results show that this method increase the accuracy of the fault diagnose.en_US
dc.description.sponsorshipIEEEen_US
dc.identifier.endpage651en_US
dc.identifier.isbn978-1-4244-0719-4
dc.identifier.startpage648en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21656
dc.identifier.wosWOS:000252924600162en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleThe detection of rotor faults by using Short Time Fourier Transformen_US
dc.typeConference Objecten_US

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