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

Abstract: In this paper, aA 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.

Key words: motor fault diagnosis, vibration signal, ensemble empirical mode decomposition (EEMD), correlation coefficient, Hilbert-Huang transform (HHT), intrinsic mode function (IMF)