基于EEMD和HHT的低压异步电动机故障诊断  

Fault Diagnosis of Low-Voltage Asynchronous Motor Based on Vibration Signal

作　　者：汤成 张懿[1,2] 魏海峰 周啸伟[2] 丁伟 TANG Cheng;ZHANG Yi;WEI Hai-feng;ZHOU Xiao-wei;DING Wei(School of Electronic Information,Jiangsu University of Science and Technology Electronic Information,School,Zhenjiang 212003,China;Changshu Ruite Electric Co.,Ltd.,Changshu 215500,China;DAQO Group Co.,Ltd.,Zhenjiang 212200,China)

机构地区：[1]江苏科技大学电子信息学院,镇江212003 [2]常熟瑞特电气股份有限公司,常熟215500 [3]大全集团有限公司,镇江212200

出　　处：《微特电机》2021年第7期44-49,56,共7页Small & Special Electrical Machines

基　　金：国家自然科学基金项目(51977101);江苏省省重点研发计划产业前瞻性与共性关键技术重点项目(BE2018007)。

摘　　要：针对船用电动机位置分散、安装环境各异,难以对全生命周期的全过程进行监测的特点,提出了一种利用电动机的振动信号、基于集合经验模态分解和希尔伯特-黄变换相结合的低压异步电动机故障诊断方法。采用集合经验模态分解方法将振动信号分解为各级本征模态函数分量,利用相关系数选取出和原振动信号有关的本征模态函数分量,再利用希尔伯特-黄变换中包络解调的方法,将选取出的本征模态函数分量进行重构,以突出故障的特征信息。经过实验表明,利用电动机的振动信号、基于集合经验模态分解和希尔伯特-黄变换相结合的低压异步电动机故障诊断方法,突出了故障特征,可以对堵转、三相不平衡等常见故障进行有效、准确的识别。A novel fault diagnosis of low-voltage asynchronous motor based on vibration signal was prosposed. Some common faults are bound to be identified based on a combination of ensemble empirical mode decomposition(EEMD) and Hilbert-Huang transform(HHT).EEMD method was used to decompose the vibration signal into intrinsic modal function(IMF) components at all levels, the correlation coefficient is used to select the IMF component related to the original vibration signal, and the Hilbert envelope demodulation method was used to highlight the fault feature information. The method of combining EEMD and HHT can not only suppress noise, but also highlight fault characteristics. The results show that the low-voltage asynchronous motor fault diagnosis method based on the combination of EEMD and HHT can effectively and accurately identify common faults.

关 键 词：电机故障诊断 振动信号 集合经验模态分解 相关系数 希尔伯特-黄变换 本征模态函数 

分 类 号：TM343[电气工程—电机]