Single-channel blind source separation based on EMD and CICA and its application to gearbox multi-fault diagnosis

被引：0
|
作者：
Hao R. [1 ]
An X. [1 ]
Shi Y. [1 ]
机构：
[1] School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang
来源：
Zhendong yu Chongji/Journal of Vibration and Shock | 2019年 / 38卷 / 08期
关键词：
Blind source separation(BSS); Constrained independent component analysis(CICA); Empirical mode decomposition(EMD); Multi-fault diagnosis;
D O I：
10.13465/j.cnki.jvs.2019.08.034
中图分类号：
学科分类号：
摘要：
Considering that the traditional independent component analysis is too difficult to solve the problems of underdetermined blind source separation (BSS) in gearbox multi-fault diagnosis, a single-channel blind source separation method based on empirical mode decomposition (EMD) and constrained independent component analysis (CICA) was proposed. Gearbox multi-fault signal was collected by a single-channel acceleration sensor, and it was decomposed by the EMD method to achieve noise reduction and single channel expansion. By virtue of the characteristics of white noise and kurtosis value, the effective IMF components were selected, which was treated as input signals for the BBS. The target vibration signal was extracted by the CICA method to identify the fault feature. A case study on gearbox bearing and gear multi-fault simulations and experiments verifies the effectiveness and feasibility of the proposed method. © 2019, Editorial Office of Journal of Vibration and Shock. All right reserved.
引用
收藏
页码：225 / 231and262
相关论文
共 11 条
  • [1] Lei Y., Kong D., Li N., Et al., Adaptive ensemble empirical mode decomposition and its application to fault detection of planetary gearboxes, Journal of Mechanical Engineering, 50, 3, pp. 64-70, (2014)
  • [2] Li H., Zhang Y., Zheng H., Application of hermitian wavelet to crack fault detection in gearbox, Mechanical Systems and Signal Processing, 25, 4, pp. 1353-1363, (2011)
  • [3] Zhang K., Cheng J., Yang Y., Order tracting analysis based on local decomposition and its application to gear fault diagnosis, China Mechanical Engineering, 22, 14, pp. 1731-1736, (2011)
  • [4] Qin L., Shi L., Zhang Y., Research of the noise removal method for mechanical vibration signal based on blind signal extraction, Electronic Measurement Technology, 32, 2, pp. 4-6, (2009)
  • [5] Lu W., Rajapakse J.C., ICA with reference, Neuro Computing, 69, 3, pp. 2244-2257, (2006)
  • [6] Wang Z.Y., Chen J., Dong G.M., Et al., Constrained independent component analysis and its application to machine fault diagnosis, Mechanical Systems and Signal Processing, 25, pp. 2501-2512, (2011)
  • [7] Wu C., Guo Y., Liang Y., Extracting fault features of rolling bearing during speed variation based on CICA, Mechanical Science and Technology, 32, 8, pp. 1176-1181, (2013)
  • [8] Liang Y., Guo Y., Wu C., Rolling element bearing fault feature extraction based on spectral kurtosis and CICA, Journal of Mechanical Strength, 35, 5, pp. 559-565, (2013)
  • [9] Huang N.E., Shen Z., Long S.R., Et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis, Proceeding of Royal Society London A, 454, pp. 903-995, (1998)
  • [10] Wu Z.H., Huang N.E., A study of the characteristics of white noise using the empirical mode decomposition method, Proceeding of Royal Society London A, 460, pp. 1597-1611, (2004)
12