A Bearing Fault Diagnosis Using Wavelet Envelope Spectrum Based on Full Vector Spectrum Technology

Abstract:

Article Preview

Wavelet envelope demodulation method can distinguish the fault information from complex bearing vibration signal. However, traditional signal analysis method, which is solely based on a single source data, is imperfect. In this paper, an approach to wavelet packet and envelope analysis based on full vector spectrum technology was proposed. Firstly, two different data from the same source were respectively decomposed and recomposed by wavelet packet transform. Then, in order to improve the accuracy of detecting fault, the recomposed signals were merged by using the full vector spectrum method. Compared to the traditional signal analysis method, the advantage of the new method is presented by showing their application to bearings. Finally, results from the bearing vibration signal analysis show that the new approach is more effective because of its inheritance and all-sided feature.

Info:

Periodical:

Edited by:

Yonghong Tan

Pages:

873-879

DOI:

10.4028/www.scientific.net/AMM.190-191.873

Citation:

X. Y. Gong et al., "A Bearing Fault Diagnosis Using Wavelet Envelope Spectrum Based on Full Vector Spectrum Technology", Applied Mechanics and Materials, Vols. 190-191, pp. 873-879, 2012

Online since:

July 2012

Export:

Price:

$35.00

[1] Michael Feldman. Hilbert transform in vibration analysis. Mechanical Systems and Signal Processing 25 (2011) 735-802.

DOI: 10.1016/j.ymssp.2010.07.018

[2] Yang Ming, Jin Chen, Guangming Dong. Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum. Mechanical Systems and Signal Processing 25 (2011) 1773-1785.

DOI: 10.1016/j.ymssp.2010.12.002

[3] N.G. Nikolaou, I.A. Antoniadis. Rolling element bearing fault diagnosis using wavelet packets. NDT& International 35(2002) 197-205.

DOI: 10.1016/s0963-8695(01)00044-5

[4] S. Abbasion, A. Rafsanjani, A. Farshidianfar, N. Irani. Rolling element bearings multi-fault classification based on the wavelet denoising and support vector machine. Mechanical Systems and Signal Processing 21 (2007) 2933-2945.

DOI: 10.1016/j.ymssp.2007.02.003

[5] HUANG DISHAN. A Wavelet-based algorithm for the Hilbert transform. Mechanical Systems and Signal Processing 10(2) (1966) 125-134.

DOI: 10.1006/mssp.1996.0009

[6] Yuh-Tay Sheen, Chun-Kai Hung. Constructing a wavelet-based envelope function for vibration signal analysis. Mechanical Systems and Signal Processing 18 (2004) 119–126.

DOI: 10.1016/s0888-3270(03)00046-3

[7] Xianfeng Fan, Ming J. Zuo. Gearbox fault detection using Hilbert and wavelet packet transform. Mechanical Systems and Signal Processing 20 (2006) 966–982.

DOI: 10.1016/j.ymssp.2005.08.032

[8] Guo-hua Zhang, Wen-juan Zhang, Peng-xiang Xue. Wavelet analysis and application. Xi'an, 2006 99-110(in Chinese).

[9] Fahri Vatansever, Ayhan Ozdemir. Power parameters calculations based on wavelet packet transform. Electrical Power and Energy Systems 31 (2009) 596–603.

DOI: 10.1016/j.ijepes.2009.04.001

[10] S.L. Hahn, Hilbert Transforms in Signal Processing, Artech House, 1996, 305.

[11] Ling-li Cui, Li-xin Gao, Guo-dong Wang. Research on the demodulation method based on the wavelet analysis. Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, Beijing, China, 2-4 Nov. 2007: 1683-1687.

DOI: 10.1109/icwapr.2007.4421724

[12] Jie Han, Laide Shi. Full vector spectrum technology and its engineering application. Beijing, 2008 9-136(in Chinese).

[13] Jie Han, Laide Shi. Study of full imformation energy spectrum analysis method of rotary machinery. Journal of Mechanical Strength, 25(2003) 364-368.

[14] Jie Han, Xinmin Dong, Wei Hao. Full information cepstrum analysis and application based on same source data of rotary machinery. Journal of Mechanical Strength, 27(2005) 452-455.

[15] Xiaoyun Gong, Jie Han, Hong Chen. Vector-Hilbert demodulation and its application in the gear failure diagnosis. Journal o Mechanical Strength 32(2010) 1008-1011.

In order to see related information, you need to Login.