基于小波分析的发电机定子绕组两相短路故障检测

Two-phase Short Circuit Faults Detection of Generator Stator Winding Based on Wavelet Analysis

针对传统的矿用发电机故障检测使用傅里叶变换无法刻画时域信息和受频率波动大的缺点,研究了基于小波分析的矿用发电机定子绕组两相短路故障检测,在获得发电机参数的基础上,搭建了具有比率式纵联差动保护的三相发电机两相短路的SIMULINK模型,就故障电阻较大、较小,频率正常、波动4种情况对差动电流分别进行傅里叶变换和小波分析,仿真结果验证了小波分析的高灵敏度和强鲁棒性,较傅里叶变换更适合用于发电机定子绕组两相短路故障的检测。

Because of conventional generator fault detection using Fourier transform, it can＇t depict the time domain information and have the disadvantages of frequency fluctuation. The paper studies two- phase faults detection of generator stator winding based on the wavelet analysis. On the basis of the generator parameters calculated, first setting up SIMULINK model of three-phase synchronous generator with percentage differential protection. According to the fault resistance is greater or the smaller,the frequency is normal or fluctuation,differential current was done Fourier transform and wavelet analysis. Simulation results show the wavelet analysis have high sensitivity and strong robustness, it is more suitable for two-phase short circuit faults detection of generator stator winding compared with Fourier transform.