Rotor Fault Detection in Squirrel Cage Induction Motors using MCSA and DWT Techniques

N. Bessous, S. Sbaa, R. Pusca, R. Romary
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Abstract

This article presents the fault detection of broken rotor bar (BRB) faults in squirrel cage induction motors (SCIMs). This work applied two diagnostic methods on stator current signal. It is necessary to verify the machine health to avoid any catastrophic damage. The first method uses the fast Fourier transform (FFT) which is generally called motor current signature analysis (MCSA). We carefully verified the spectral content of the stator current to detect BRB fault. The new harmonics allows us to take a good decision about BRB fault. The second method is based on the discrete wavelet transform (DWT). This technique is widely used in the diagnosis field of rotating machinery. According to DWT method, we used the mean square error (MSE) as a good indicator. An experimental test with different conditions of the induction motor has been performed. The experimental results have been exploited using MCSA and DWT methods to achieve a good decision.
基于MCSA和DWT技术的鼠笼式异步电动机转子故障检测
介绍了鼠笼式异步电动机转子断条故障的故障检测方法。本文采用两种方法对定子电流信号进行诊断。有必要验证机器的健康状况,以避免任何灾难性的损坏。第一种方法使用快速傅里叶变换(FFT),通常称为电机电流特征分析(MCSA)。我们仔细验证了定子电流的频谱含量,以检测BRB故障。新谐波可以帮助我们更好地判断BRB故障。第二种方法基于离散小波变换(DWT)。该技术广泛应用于旋转机械的诊断领域。根据DWT方法,我们使用均方误差(MSE)作为一个很好的指标。对异步电动机进行了不同工况下的实验测试。利用MCSA和DWT方法对实验结果进行了比较,取得了较好的决策效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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