Fault Diagnosis Method of Gear Based on Local Mean Decomposition and Least Squares Support Vector Machine

Abstract:

For differences of time-domain energy distribution of different gear fault vibration signal, an analytical method based on local mean decomposition (LMD) and least squares support vector machine (LS-SVM) is proposed to apply to gear fault diagnosis. First vibrational signal of gear is decomposed into a series of product functions (PF) by LMD method. Then extracting energy characteristic parameters of PF components which contain main fault information to constitute a fault feature vectors, which is considered as input sample of well-trained LS-SVM, and then identifying working state and fault type of different gear can be identified accurately and effectively by diagnostic method based on LMD and LS-SVM.

• Periodical: Applied Mechanics and Materials (Volume 415)
• Pages: 548-554
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.415.548
• Online since: September 2013
• Authors: Zhou Wan, Xing Zhi Liao, Xin Xiong, Zhi Rong Li
• Keywords: Fault Diagnosis, Gear, Least Squares Support Vector Machines (Ls-SVM), Local Mean Decomposition (LMD)

References

[1] Huang N E, Wu M-L C, Long S R. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis[J]. Proc. R. Soc. Lond. A, 2003, 459: 2317-2325.

DOI: 10.1098/rspa.2003.1123

[2] Yongjun Deng, Wei Wang．Boundary processing technique in EMD method and Hilbert transform[J]．Chinese Scfence Bulletin, 2001, 46(11): 257-263.

[3] Jun-sheng Cheng, De-jie Yu, Yu Yang. Research on the intrinsic mode function(IMF)criterion in EMD method[J]．Mechanical Systems and Signal Processing, 2006, 20(4): 817-824.

DOI: 10.1016/j.ymssp.2005.09.011

[4] Qin S R, Zhong Y M. A new algorithm of Hilbert-Huang transform [J]. Mechanical Systems and Signal Processing, 2006, 20(8): 1941-(1952).

DOI: 10.1016/j.ymssp.2005.07.002

[5] JONATHAN S. Smith. The local mean decomposition and its application to EEG perception data [J]. Journal of the Royal Society Interface, 2005, 2(5): 443-454.

DOI: 10.1098/rsif.2005.0058

[6] Jun-sheng Cheng, Mei-li Shi, Yu Yang. The method of roller bearing fault diagnosis based on LMD and neural network [J]. Journal of Vibration and Shock, 2010, 29(8): 141-144.

[7] Zhi-nong Li, Wei-bing Liu, Xiao-bing Yi. the method of mechanical failure underdetermined blind source separation based on local mean decomposition [J]. Journal of Mechanical Engineering, 2011, 47(7): 97-102.

DOI: 10.3901/jme.2011.07.097

[8] Jun-sheng Cheng, Kang Zhang, Yu Yang. Ensemble local mean decomposition method based on noise-assisted analysis [J]. Journal of Mechanical Engineering, 2011, 47(3): 55-62.

DOI: 10.3901/jme.2011.03.055

[9] Zhang Quan-ming, Liu Hui-jin. Application of LS-SVM in Classification of Power Quality Disturbances[J]. Proceedings of the CSEE, 2008, 28 (1): 106-110.

[10] Li Yu-jun, Tang Xiao-jun, Liu Jun-hua. Application of Least Square Support Vector Machine Based on Particle Swarm Optimization in Quantitative Analysis of Gas Mixture[J]. Spectroscopy and Spectral Analysis, 2010, 30(3): 774-778.

DOI: 10.3724/sp.j.1096.2012.10898