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Detection and classification of winding faults in windmill generators using wavelet transform and ANN

Zervakis Michalis, Stavrakakis Georgios, Zacharias E. Gketsis

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/E919C475-D816-44A0-BCB9-A8B14562BAB9-
Αναγνωριστικόhttps://doi.org/10.1016/j.epsr.2009.05.001-
Γλώσσαen-
Μέγεθος12 pagesen
ΤίτλοςDetection and classification of winding faults in windmill generators using wavelet transform and ANNen
ΔημιουργόςZervakis Michalisen
ΔημιουργόςΖερβακης Μιχαληςel
ΔημιουργόςStavrakakis Georgiosen
ΔημιουργόςΣταυρακακης Γεωργιοςel
ΔημιουργόςZacharias E. Gketsis en
ΕκδότηςElsevieren
ΠερίληψηThis paper exploits the Wavelet Transform (WT) analysis along with Artificial Neural Networks (ANN) for the diagnosis of electrical machines winding faults. A novel application is presented exploring the problem of automatically identifying short circuits of windings, which often appear during machine manufacturing and operation. Such faults are usually resulting from electrodynamics forces generated during the flow of large short circuit currents, as well as forces occurring when the machines are transported. The early detection and classification of winding failures is of particular importance, as these kinds of defects can lead to winding damage due to overheating, imbalance, etc. Application results and investigations of windmill generator winding turn-to-turn faults between adjacent winding wires are presented. The ANN approach is proven effective in detecting and classifying faults based on WT features extracted from high frequency measurements of the admittance, current, or voltage responses.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-23-
Ημερομηνία Δημοσίευσης2009-
Θεματική ΚατηγορίαEngineering, Mechanicalen
Θεματική Κατηγορίαmechanical engineeringen
Θεματική Κατηγορίαengineering mechanicalen
Βιβλιογραφική Αναφορά ANN Z.E. Gketsis, M.E. Zervakis, G. Stavrakakis ," Detection and classification of winding faults in windmill generators using wavelet transform and ANN ," Electric Power Syst. Res.,vol. 79,no.11 ,pp. 1483-1494,2009.doi:10.1016/j.epsr.2009.05.001en

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