基于小波包变换的牵引电机转子断条隐患特征提取方法研究  

Research on the Feature Extraction Method for Rotor Bar Broken Fault of Traction Motor Based on Wavelet Packet Transform

作　　者：钱存元[1] 阙龙凯[1] 梁海泉[1] 

机构地区：[1]同济大学铁道与城市轨道交通研究院,上海201804

出　　处：《机电一体化》2013年第9期23-27,95,共6页Mechatronics

基　　金：国家63计划(编号:2011AA110501)

摘　　要：为了实现城轨列车牵引电机在运行时故障隐患的实时监控,根据牵引电机实际运行情况,在Matlab/Simulink仿真环境中建立起了处在闭环控制系统中的带有转子断条隐患的异步电机模型。对定子侧三相电流进行小波包分解并对各频段信号进行小波包系数重构,计算各频段的能量特征值,最后构建出隐患特征向量对电机转子隐患做出诊断。通过对仿真数据的应用,利用上述方法可以有效地识别出电机的转子断条隐患,为研制地铁列车牵引电机隐患挖掘与评估预警系统提供了技术参考。To detect the potential faults of running rail traction motor in real time, a model of traction motor with broken rotor bars in the closed-loop control system is built in Matlab/Simulink according to its actual working conditions. The 3-phase stator currents are decomposed by wavelet packet functions and all the wavelet packet coefficients of each frequency bands are reconstructed. Then all the energy eigenvalues are calculated to constitute the eigenvectors that can diagnose rotor faults. Through applying the proposed method to the simulation data, the hidden fault of rotor bar broken of traction motor can be effectively identified. And the research results also provide technical reference for the hidden fault mining and evaluating system for the rail traction motor in the future.

关 键 词：牵引电机 闭环系统 转子断条 小波包 能量特征值 故障识别 

分 类 号：TM922.71[电气工程—电力电子与电力传动]