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Fault Monitoring and Diagnosis of Induction Machines Based on Harmonic Wavelet Transform and Wavelet Neural Network

机译:基于谐波小波变换和小波神经网络的异步电机故障监测与诊断

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The fault symptoms of stator winding inter-turn short circuit and rotor bar breakage are analyzed completely in this paper. And a new method for fault diagnosis of broken rotor bar and inter-turn short-circuits in induction machines is presented. The method is based on the analysis of the motor current signature analysis of induction machines using Zoom FFT spectrum analysis, generalized harmonic wavelet transform filter and hybrid particle swarm optimization (HPSO) based wavelet neural network. As an on-line current monitoring and non-invasive detection scheme, the presented method yields a high degree of accuracy in fault identification as evidenced by the given experimental results, which demonstrate that the detection scheme is valid and feasible.
机译:本文完全分析定子绕组绕组短路和转子杆断裂的故障症状。提出了一种新的损坏转子杆的故障诊断方法以及感应机器中的匝间短路。该方法基于使用变焦FFT频谱分析,广义谐波小波变换滤波器和混合粒子群优化(HPSO)小波神经网络的电动机电流签名分析的分析。作为在线电流监测和非侵入性检测方案,所提出的方法在故障识别中产生高精度,如给定的实验结果所证明,这表明检测方案有效和可行。

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