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Diagnostic des défauts des machines asynchrones par reconnaissance des formes

Abstract : Advances in power electronics, control circuits and automatic have contributed to an increasing use of induction motors in electrical drive systems. The large – scale utilization of induction motors is mainly due to their robustness, their power – weight ratio, and to their manufacturing cost. Therefore, it is important to develop diagnosis tools in order to detect earlier the faults, which can appear in these machines. Our approach is based on pattern recognition methods. A vector of parameters, called pattern vector, is obtained from the measurements made on the machine. The decision rules enable to classify the observations described by the pattern vector. These classifications are made according to the different operating conditions, with or without fault. Faults have been created on both the rotor and the stator sides of the induction machine. This one was fed either from the mains, or from a three – phase voltage inverter. Fault detection has been made with decision procedures based on the k – nearest neighbors rule and on boundaries direct calculation. The results obtained with these algorithms have proved the efficiency of pattern recognition methods for diagnosis.
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Submitted on : Tuesday, April 3, 2007 - 11:35:24 AM
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  • HAL Id : tel-00139706, version 1


Roland Casimir. Diagnostic des défauts des machines asynchrones par reconnaissance des formes. Autre. Ecole Centrale de Lyon, 2003. Français. ⟨tel-00139706⟩



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