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.
出处
《煤矿机电》
2013年第6期16-18,23,共4页
Colliery Mechanical & Electrical Technology
关键词
混沌理论
故障诊断
相空间重构
关联维数
Chaos theory
fault diagnosis
phase space reconstruction
correlation dimension
