基于模型与BPNN感应电机定子匝间故障定位方法

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Abstract In order to detect and locate an inter-turn short circuit fault on the stator windings of induction motors, an approach based on faulty model and BP neural network(BPNN)is presented. The diagnostic process can be achieved through monitoring both simultaneously the values of the three-phase current root mean square(rms)and three-phase shifts between the line current and the phase voltage of the machine. By analysis, it is rapid and accurate to choose three-phase shifts as inputs for the BPNN of the diagnostic system. For improving dynamical processing ability, genetic algorithm is adopted to optimize the BP neural network parameters. Simulation and experimental results have verified the validity of the method.

Key words： keywords：Induction motor inter-turn short circuit fault location phase shift BP neural network genetic algorithm

Received: 10 September 2012 Published: 12 December 2013

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	Wang Xuhong
	He Yigang
	Wang Kunyang

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Wang Xuhong,He Yigang,Wang Kunyang. An Approach for Location of Stator Interturn Faults in Induction Motor Based on the Model and Neural Network[J]. Transactions of China Electrotechnical Society, 2013, 28(1增): 336-345.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2013/V28/I1增/336

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