Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 55, Issue 12, Pages 4277-4289Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2008.2004667
Keywords
Diagnosis; induction machine; interturn short circuit; neural network (NN); phase shifts
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Funding
- Comite Mixte Franco-Tunisien de Cooperation Universitaire (CMCU) [CMCU 04/S 1122]
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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.
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