Induction Motor Stator Faults Diagnosis by a Current Concordia Pattern Based Fuzzy Decision System

Abstract : This paper deals with the problem of detection and diagnosis of induction motor faults. Using the fuzzy logic strategy, a better understanding of heuristics underlying the motor faults detection and diagnosis process can be achieved. The proposed fuzzy approach is based on the stator current Concordia patterns. Induction motor stator currents are measured, recorded and used for Concordia patterns computation under different operating conditions, particularly for different load levels. Experimental results are presented in terms of accuracy in the detection motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia patterns.
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Fatiha Zidani, Mohamed Benbouzid, Demba Diallo, Mohamed-Saïd Naït-Saïd. Induction Motor Stator Faults Diagnosis by a Current Concordia Pattern Based Fuzzy Decision System. IEEE Transactions on Energy Conversion, Institute of Electrical and Electronics Engineers, 2003, 18 (4), pp.469-475. ⟨hal-01052445⟩

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