针对有源电力滤波器APF(active power filter)逆变器中IGBT易发生故障的问题,提出了基于故障特征提取的有源电力滤波器故障诊断方法。构建了APF故障仿真模型和基于小波包分析的故障特征提取方法,仿真分析了APF网侧电流波形,并运用小波包分析对IGBT故障时的网侧电流波形进行处理,提取了IGBT故障特征向量,最后运用神经网络对特征向量的分类来实现对APF的故障诊断。在APF故障诊断系统上进行测试,验证了该诊断方法的有效性和可行性。
英文摘要:
For the sake of easily damaged characteristic of IGBT in the inverter, a method to diagnose the fault of APF was proposed based on fault feature extraction. The model of APF fault simulation and the method of the feature extraction based on the wavelet packet analysis were established, the waveforms of grid side current were simulated, analysed the waveforms of grid side current of IGBT open circuit fault by wavelet packet analysis, extracted the fault features vector. Finally, the classification function of the neural network was applied for the APF fault diagnosis. The effectiveness and feasibility of the diagnosis method are validated by test results of APF fault diagnosis system.