城轨车辆辅助逆变器IGBT状态识别研究

Research on IGBT in Auxiliary Inverter of Urban Rail Vehicles State Recognition

摘要:

提出一种基于小波包分解和马氏距离的IGBT状态识别方法,并应用于地铁车辆辅助逆变电路。首先建立Matlab电路模型,分别对该电路的不同故障临界状态和正常状态进行仿真分析,提取输出电流信号进行小波包分解得到信号特征向量,作为特征样本。利用特征样本计算各临界故障与正常情况下的马氏距离,作为识别阈值。实际应用时,将待测电路与正常状态做马氏距离,对比阈值区间完成电路状态识别。实验表明,此方法能简单有效检测区分软硬故障,实现IGBT状态识别。

Abstract:

Based on Wavelet packet decomposition and Mahalanobis distance, a method of IGBT state recognition applied to urban rail vehicles auxiliary inverter circuit is proposed. Firstly, establishing the Matlab circuit model, simulating and analyzing the abnormal states and normal state, the eigenvectors of the output current signal is obtained for wavelet packet decomposition. After obtaining the characteristic samples in different circuit states, the characteristic samples are used to calculate the Mahalanobis distance of each critical fault and normal condition, then the recognition threshold is obtained. In practical application, calculate the distance between the circuit to be measured and the normal state with Mahalanobis distance, and then compare the threshold interval to complete the circuit state recognition. The results shows that the method can directly recognize IGBT state, distinguish the parameter fault and the structural fault.