Induction motor rotor fault detection using Artificial Neural Network

Rakeshkumar A. Patel, B. Bhalja
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引用次数: 8

Abstract

The present paper deals with the detection of broken rotor bar of an induction motor. The problem is approached through mathematical modeling of induction motor. Both the models, for healthy as well as faulty motor, are developed using MATLAB simulink. The model is used to simulate different conditions of fault with varying number of broken bars. Parameters like three-phase voltage, three-phase current and THD of all voltages and currents are acquired from the simulated model. The data thus generated is used to train Artificial Neural Network which diagnoses the condition of motor. The results obtained prove the effectiveness of proposed method.
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基于人工神经网络的感应电机转子故障检测
本文研究了感应电动机转子断条的检测问题。通过对感应电机进行数学建模,探讨了该问题。利用MATLAB simulink建立了正常电机和故障电机的模型。该模型用于模拟不同断条数的不同故障情况。从仿真模型中获取各电压、电流的三相电压、三相电流、THD等参数。生成的数据用于训练人工神经网络来诊断电机的状态。仿真结果证明了该方法的有效性。
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