In this article, a threshold-based induction motor fault diagnosis method is proposed using the measured stator current signal. A 0.25-HP three-phase squirrel-cage induction motor fed directly online is tested in the laboratory with various single- and multielectrical faults under six different loading conditions. The discrete wavelet transform (DWT) is chosen as the signal processing technique for the measured stator currents. The threshold and energy values at each decomposition level of the DWT processing results are evaluated. Threshold values appear to be more consistent than energy values at different measured data windows, and thus, the threshold at the decomposition level d8 is chosen as a fault indicator. Curve fitting equations are developed to calculate threshold values for the motor loadings that were not tested in experiments. The suitability using threshold values for induction motor fault diagnosis is further validated using two probabilistic methods, the correlation analysis and the confidence interval estimation.

中文翻译：

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使用离散小波变换和测量定子电流信号的基于阈值的感应电机单故障和多故障诊断

在本文中，提出了一种基于测量定子电流信号的基于阈值的感应电机故障诊断方法。一台直接在线供电的 0.25-HP 三相鼠笼式感应电机在实验室中在六种不同负载条件下进行了各种单电和多电故障的测试。离散小波变换 (DWT) 被选为测量定子电流的信号处理技术。对 DWT 处理结果的每个分解级别的阈值和能量值进行评估。阈值似乎比不同测量数据窗口的能量值更一致，因此，选择分解级别 d8 的阈值作为故障指标。开发了曲线拟合方程来计算未在实验中测试的电机负载的阈值。