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Induction motor rotor fault detection using Artificial Neural Network

机译:使用人工神经网络感应电动机转子故障检测

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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.
机译:本文涉及检测感应电动机的破损转子杆。通过感应电动机的数学建模来解决问题。使用MATLAB Simulink开发出型号,适用于健康的电机以及缺陷的电动机。该模型用于模拟不同数量的断杆的不同故障条件。从模拟模型获取三相电压,三相电压,三相电流和电流的三相电流和THD。由此产生的数据用于培训诊断电动机状况的人工神经网络。得到的结果证明了所提出的方法的有效性。

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