The Identification Technology of Rolling Bearing Acoustic Emission Fault Pattern Based on Redundant Lifting Wavelet Packet and SVM

Abstract:

As the energy distribution in each frequency band of rolling bearing acoustic emission (AE) signal is related to its fault type, so we can use the redundant lifting wavelet packet to decompose the rolling bearing AE signal of different fault into different frequency band, combine energy in each frequency band together to be a feature vector of the Support Vector Machines (SVM), then being applied to identify the fault through SVM. This paper also compared the redundant lifting wavelet packet and Daubechies wavelet packet as well as the SVM and neural networks. The experimental result shows that for the fault pattern identification, the method that combines redundant lifting wavelet packet decomposition and SVM together can be effective.

• Periodical: Applied Mechanics and Materials (Volumes 52-54)
• Pages: 2033-2038
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.52-54.2033
• Online since: March 2011
• Authors: Li Xin Gao, Fen Lou Zhai, Bang Xi Hu, Jiang Hua Zhou, Jian Hua Chen, Yong Gang Xiao
• Keywords: Acoustic Emission (AE), Fault Pattern Identification, Redundant Lifting Wavelet Packet, Rolling Bearing, Support Vector Machine (SVM)

References

[1] Jack LB; Nandi AK; McCormick A C. Diagnosis of rolling element bearing faults using radial basis function net works. Applied Signal Processing, 1999, 6, 25-32.

DOI: 10.1007/s005290050031

[2] Li Ling-jun; Zhang Zhou-suo; He Zheng-jia. Research of Mechanical System Fault Diagnosis Based on Support Vector Data Description. Journal of xi an jiiaotong university, 2003, 37, 910-913.

[3] Li Gang; Xing Shu-bao; Xue Hui-feng. Comparison on pattern analysis performance of SVM and RVM based on RBF kernel. Application Research of Computers, 2009, 26, 1782-1784.

[4] Ezenwoyeo; Masoud Sadjadis; Robust BP EL2. Transparent autonomization in business processes through dynamic proxies. Proc of the 8th International Symposium on Autonomous Decentralized Systems, 2007, 17-24.

DOI: 10.1109/isads.2007.65

[5] Zhu Ying-hui; Li You-long; Liu An-zhong. SVM apply in small sample gear fault diagnosis. Coal Mine Machinery, 2006, 5, 48-51.