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AuthorRefaat, Shady S.
AuthorAbu-Rub, Haitham
AuthorSaad, M.S.
AuthorAboul-Zahab, E. M.
AuthorIqbal, Atif
Available date2015-06-25T10:22:58Z
Publication Date2013-03
Publication NameTwenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition (APEC) 2013
CitationRefaat, Shady S.; Abu-Rub, Haitham; Saad, M.S.; Aboul-Zahab, E.M.; Iqbal, Atif, "Fault Tolerance of Stator Turn Fault for Three Phase Induction Motors Star-Connected Using Artificial Neural Network," Applied Power Electronics Conference and Exposition (APEC), 2013 Twenty-Eighth Annual IEEE , vol., no., pp.2336,2342, 17-21 March 2013
ISBN978-1-4673-4354-1
ISSN1048-2334
URIhttp://dx.doi.org/10.1109/APEC.2013.6520621
URIhttp://hdl.handle.net/10576/3389
AbstractThis paper proposes the possibility of developing incipient fault diagnosis and remedial operating strategies, which enable a fault tolerant induction motor star-connected winding with neutral point earthed through a controllable impedance using artificial neural network (ANN). The fault detection and diagnosis is achieved by using a strategy that detects stator turn fault, isolates the faulty components, identifies fault severity and reduces the propagation speed of the incipient stator winding fault. The fault tolerance is obtained by controlled neutral grounding resistor. This allows for continuous free operation of the induction motor even with stator winding faults. The advantage of this strategy is that it does not require any change in the standard drive system. Experimental results demonstrate the validity of the proposed technique.
SponsorQatar National Research Fund NPRP 08-369-2-140
Languageen
PublisherIEEE
SubjectElectric motors, Induction
SubjectFault tolerance (Engineering)
TitleFault Tolerance of Stator Turn Fault for Three Phase Induction Motors Star-Connected Using Artificial Neural Network
TypeConference Paper


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