基于EMD的鼠笼式异步电动机偏心故障诊断研究  

Study on Eccentricity Fault Diagnosis of Cage Induction Motor Based on EMD

作　　者：许允之[1] 赵月南[2] 郭西进[1] 孔利利[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]浙江大学电气工程学院,浙江杭州310000

出　　处：《煤矿机电》2014年第5期5-9,共5页Colliery Mechanical & Electrical Technology

摘　　要：在经验模态分解鼠笼式异步电动机横向、纵向振动信号的基础上,得出合理的内禀模态分量,分离信号的频率族,取得物理意义的频率分辨效果。再对各分量进行Hilbert变换,并分析信号的Hilbert边际谱,找出偏心故障电动机的特征频率成分。研究表明,用HHT方法能够很好提取偏心电动机故障的特殊故障频率。Based on EMD （Empirical Mode Decomposition ） of the horizontal and vertical signals of the asynchronous cage induction motor, the reasonable intrinsic mode components could be obtained for separating the frequency families and reaching the physical frequency differentiating effect. Then the Hilbert transformation for each intrinsic mode component of the motor with eccentricity fault is found out through Hilbert marginal spectrum analysis of signal. The study shows that the HHT （ Hilbert-Huang Transformation） method is preferred to extract the characteristic fault frequency of the motor with eccentricity fault.

关 键 词：故障诊断 异步电动机 边际谱 希尔伯特-黄变换(HHT) 

分 类 号：TM343.3[电气工程—电机] TP277.3[自动化与计算机技术—检测技术与自动化装置]