Detection of bearing defects in three-phase induction motors using Park’s transform and radial basis function neural networks |
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Authors: | Izzet Y Önel K Burak Dalci İbrahim Senol |
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Affiliation: | (1) Electrical-Electronics Faculty, Electrical Engineering Department, Yildiz Technical University, Besiktas, 34349 Istanbul, Turkey |
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Abstract: | This paper investigates the application of induction motor stator current signature analysis (MCSA) using Park’s transform
for the detection of rolling element bearing damages in three-phase induction motor. The paper first discusses bearing faults
and Park’s transform, and then gives a brief overview of the radial basis function (RBF) neural networks algorithm. Finally,
system information and the experimental results are presented. Data acquisition and Park’s transform algorithm are achieved
by using LabVIEW and the neural network algorithm is achieved by using MATLAB programming language. Experimental results show
that it is possible to detect bearing damage in induction motors using an ANN algorithm. |
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Keywords: | Induction motor stator current bearing damage Park’ s transform RBF neural network |
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