基于希尔伯特和傅立叶变换的笼型感应电动机转子断条故障检测

Detection of Broken Fault of Squirrel-Cage Induction Motor Rotor Bar Based on Hilbert and Fourier Transforms

针对笼型感应电动机转子断条故障时,频率为(1±2s)f1的故障特征分量容易被基频f1分量所淹没的特点,提出了一种基于希尔伯特变换和连续傅立叶变换的转子断条故障检测新方法。通过定子电流信号作希尔伯特变换取得反映转子断条故障特征的调制信号,然后再滤掉直流分量,最后进行连续细化傅立叶变换,以调制信号的频谱中是否存在2sf1频率分量来判断转子是否发生断条故障。仿真结果表明该方法具有可行性。

For the characteristics of squirrel-cage induction motor rotor bar with broken fault, i.e. the fault characteristic frequency （1±2s）f1 component is easily overwhelmed by the fundamental frequency f1 component, this paper proposes a new method to detect broken fault of rotor bar based on Hilbert transform and continuous Fourier transform. It obtains the modulation signal （which reflect the characteristics of broken rotor bar fault） by Hilbert transform of stator current signal, filters out the DC component, and finally carries out continuously-refined Fou- rier transform. The spectrum of modulation signal frequency 2sf1 component is used to determine whether the rotor bar is broken. The simulation results show that this method is feasible.