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Criterion function for broken-bar fault diagnosis in induction motor under load variation using wavelet transform

机译:小波变换在负荷变化下感应电动机断条故障诊断的判据函数

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摘要

In this article, a novel criterion function is introduced to diagnose the breakage in rotor bars of induction motors. This criterion function facilitates the precise diagnosis of the fault in induction motors under load variation. It uses wavelet transform to process the stator current signal in the faulty induction motors to extract the wavelet coefficients in a specific frequency band. Furthermore, spectrum analysis of the stator current around the fundamental frequency current is used to diagnose the fault non-invasively. It is shown that the amplitudes of the frequency harmonics components (1 2ks)fs are increased due to the load increases. A time-stepping finite element method is used for modeling the faults in induction motors. In this modeling, the effects of the spatial distribution of the stator winding, nonuniform air-gap permeance, geometrical and physical characteristics of different parts of the motor, and, finally, nonlinearity of the core materials are taken into account. The proposed algorithm is applied to the stator current of a healthy and a faulty induction motor. The simulation results are obtained, and their accuracy is verified by the experimental results.
机译:在本文中,引入了一种新颖的判据函数来诊断感应电动机的转子条中的破损。该标准功能有助于精确诊断负载变化下的感应电动机故障。它使用小波变换处理故障感应电动机中的定子电流信号,以提取特定频带中的小波系数。此外,对基频电流周围的定子电流进行频谱分析可用于非侵入式诊断故障。结果表明,由于负载的增加,频率谐波分量(1 2ks)fs的幅度增加了。采用时步有限元方法对异步电动机的故障进行建模。在此模型中,考虑了定子绕组的空间分布,不均匀的气隙磁导率,电动机不同部分的几何和物理特性以及最后,铁心材料的非线性的影响。该算法被应用于健康和故障感应电动机的定子电流。获得了仿真结果,并通过实验结果验证了其准确性。

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