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An Effective Neural Approach for the Automatic Location of Stator Interturn Faults in Induction Motor

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5 Author(s)
Bouzid, M. ; Lab. des Syst. Electriques, Ecole Nat. d''Ing. de Tunis, Tunis ; Champenois, G. ; Bellaaj, N.M. ; Signac, L.
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This paper presents a neural approach to detect and locate automatically an interturn short-circuit fault in the stator windings of the induction machine. The fault detection and location are achieved by a feedforward multilayer-perceptron neural network (NN) trained by back propagation. The location process is based on monitoring the three-phase shifts between the line current and the phase voltage of the machine. The required data for training and testing the NN are experimentally generated from a three-phase induction motor with different interturn short-circuit faults. Simulation, as well as experimental, results are presented in this paper to demonstrate the effectiveness of the used method.

Published in:

Industrial Electronics, IEEE Transactions on  (Volume:55 ,  Issue: 12 )

Date of Publication:

Dec. 2008

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