基于相空间重构理论的电动机匝间短路故障诊断研究  

Diagnosis Study of Turn to Turn Short Circuit in Motor Based on Phase Space Reconstruction Theory

作　　者：张晓春[1] 付焱晶[2] 马宏文[1] 许允之[1] 

机构地区：[1]中国矿业大学信息与电气工程学院,江苏徐州221116 [2]中国人民解放军海军飞行学院教研部,辽宁葫芦岛125001

出　　处：《煤矿机电》2013年第6期16-18,23,共4页Colliery Mechanical & Electrical Technology

摘　　要：为解决电动机故障诊断问题,通过采集匝间短路电流,运用互信息理论选择延迟时间,用Cao方法选择嵌入维数,对信号进行相空间重构,有效辨识不同匝间短路电阻值和不同负载下的故障信号,提出了一种辨识故障信号的方法。研究表明,混沌理论在电动机故障诊断领域具有很大优越性,并能在一定程度上填补一般线性诊断方法的空白。In order to diagnose the motor fault, the phase space reconstruction of signal is carried out by collecting turn to turn short circuit, deciding delay time by mutual information theory, and selecting embedding dimension by Cao method. The method effectively recognizes the fault signals under different turn layer short resistance and under different loads of the motor. Therefore, the study poses a recognition method for fault signals, which proves the great superiority of Chaos theory in the field of motor fault diagnosis, and fills, to a certain extent, the blank of the general linear diagnosis methods.

关 键 词：混沌理论 故障诊断 相空间重构 关联维数 

分 类 号：TM343.2[电气工程—电机]