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Warianty tytułu
Application of radial neural network for detection of faults in induction motor stator winding
Języki publikacji
Abstrakty
The paper presents application of the radial neural network for detection of faults in induction motor stator winding. The decision of stator winding condition has been taken using the artificial neural network with radial basis function based on axial flux. The axial flux has been measured for different configuration of stator winding. It can be concluded that the axial flux can be used in detection of faults in induction motor stator winding.
Czasopismo
Rocznik
Tom
Strony
93--96
Opis fizyczny
Bibliogr. 5 poz., rys., tab.
Twórcy
autor
- Instytut Elektrotechniki i Elektroniki Przemysłowej, Politechnika Poznańska, ul. Piotrowo 3A, 60-965 Poznań, wojciech.pietrowski@put.poznan.pl
Bibliografia
- [1] Intesar A., Manzar A., Comparison of Stator Current, Axial leakage Flux and Instantaneous Power to Detect Broken Rotor Bar Faults in Induction Machines. 2008 Australasian Universities Power Engineering Conference.
- [2] Kamiński M., Orłowska-Kowalska T., Kowalski Cz. T., Zastosowanie radialnych sieci neuronowych w detekcji uszkodzeń wirnika silnika indukcyjnego, Politechnika Wrocławska, Wrocław Zeszyty Problemowe – Maszyny Elektryczne Nr 84/2009.
- [3] Acosta G.G. , Verucchi C.J., Gelso E.R., A current monitoring system for diagnosing electrical failures in induction motors, Elsevier Mechanical Systems and Signal Processing 20 (2006), pp. 953–965.
- [4] Bacha K., Henaob H., Gossa M., Capolino G.-A., Induction machine fault detection using stray flux EMF measurement and neural network-based decision, Elsevier Electric Power Systems Research 78 (2008), pp. 1247–1255.
- [5] Matlab, Neural Network Toolbox, ver. 2008a.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS2-0057-0029