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A New Fault Detection Method of Induction Motor

机译:感应电动机故障检测的新方法

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摘要

According to the shortcoming that the Extended Kalman filter (EKF) method can only estimate the speed and rotor position of induction motors in time domain when it is used to diagnose the fault existed in induction motor. A new multi-scale default diagnosing method is developed by combining EKF and wavelet transform. By monitoring the voltages and currents of the stator, it is possible to estimate the speed and position on-line. The new filter combines the merit of EKF and wavelet, and it not only possesses the multiscale analysis capability both in time domain and frequency domain, but also has better estimation accuracy than traditional EKF. Computer simulation shows the effect of the new algorithm.
机译:针对该缺点,扩展卡尔曼滤波(EKF)方法只能用于诊断异步电动机中存在的故障,只能在时域内估计异步电动机的速度和转子位置。结合EKF和小波变换,开发了一种新的多尺度默认诊断方法。通过监视定子的电压和电流,可以在线估计速度和位置。新的滤波器结合了EKF和小波的优点,不仅具有时域和频域的多尺度分析能力,而且比传统的EKF具有更好的估计精度。计算机仿真显示了新算法的效果。

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