基于解析小波变换和Hilbert模量频谱分析的感应电动机转子断条故障诊断

Broken Rotor Bar Faults Diagnosis of Induction Motor Based on Analytic Wavelet Transform and Spectrum Analysis of Hilbert Modulus

针对感应电动机转子断条故障诊断会受负荷波动影响以及故障频率容易被基波成分湮没的问题,本文提出基于解析小波变换和Hilbert模量频谱分析的感应电动机转子断条故障诊断方法。首先对感应电动机的定子电流信号进行解析小波变换,判断负荷是否波动;然后根据负荷波动的定位信息提取位于负荷平稳时间段内的定子电流信号,构造此负荷平稳时间段内的定子电流信号的Hilbert模量,对其做频谱分析,判断是否含有2sf_1频率分量,以确定感应电动机是否发生转子断条故障。仿真结果表明了这种基于解析小波变换和Hilbert模量频谱分析的感应电机转子断条故障诊断方法的有效性。

Because the load fluctuation effects the broken rotor bars fault diagnosis of the induction motor and broken rotor bars fault frequency is easy to be inundated by base wave components, a fault diagnosis method of induction motor broken rotor bars was put forward based on analytic wavelet transform and Hilbert modulus spectrum analysis. Firstly, the analytic wavelet transform of the stator current signal of the induction motor was analysed to judge whether the load was fluctuated.Then the stator current signal located in load stable period was extracted according to the location information of the load fluctuations and the Hilbert modulus of the stator current signal in the load stable period were constructed. After the spectrum analysis, the frequency component 2sf1 was judged to determine whether broken rotor bar faults of induction motor occured. The effectiveness of this method was proved by the simulation result.