摘  要：在对感应电机进行故障诊断的时候，扩展卡尔曼滤波器（EKF）只能在时域上估计电机转子的位置和速度。针对这一不足，提出了一种基于EKF和小波变换的多尺度诊断方法；通过测量电机的端电压和定子线圈电流在线估计电机转子的位置和速度。新算法结合了EKF和小波变换的优点，不仅能够分析出系统在频域上的特性，而且估计精度还要优于EKF。仿真结果说明了新算法的正确性和有效性。
关键词：感应电动机；多尺度分析；扩展卡尔曼滤波；小波变换；故障诊断；仿真

Abstract: The EKF method can estimate the speed and rotor position of induction motors only in time domain when it is used to diagnose the fault existed in induction motor.To conquer the limitation,based on EKF and wavelet transform,presented a multi-scale diagnosing method.By monitoring the voltages and current of the stator,it is possible to estimate the speed and position on-line.The new filter combined 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.Simulation showed the effect of the new algorithm.
Key Words: Induction motor;Multi-scale analysis;Extended kalman filter;Wavelet transform;Fault detetion;Simulation