A Novel Approach for Detection of Bearing Defects from Noisy Vibration Signal

Abstract:

Vibration signal of a defective bearing carries fault related information. The aim of this paper is to develop a signal processing methodology that identifies the presence of defect from bearing vibration signal subjected high background noise. A simulated vibration signal considering inner race defect in a deep groove ball bearing with low signal to noise ratio has been generated and investigated. A technique involving CWT of vibration signal and post-processing though FFT has been adopted to analyze the signal. Results show that proposed methodology can yield the presence of inner race defect prominently from a noisy vibration signal.

• Periodical: Applied Mechanics and Materials (Volumes 592-594)
• Pages: 2001-2005
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.592-594.2001
• Online since: July 2014
• Authors: Deepak Paliwal*, Achintya Choudhury, T. Govardhan, Saurabh Singh Chandrawat
• Keywords: Fault Diagnosis, FFT, Rolling Element Bearing, Vibration Signal Processing

References

[1] T. A. Harris: Rolling Bearing Analysis (John Wiley and Sons, New York 2001).

[2] N. Tandon: A comparison of some vibration parameters for the condition monitoring of rolling element bearings, Measurement, Vol. 12 (1994), pp.285-289.

DOI: 10.1016/0263-2241(94)90033-7

[3] J. Archambault, R. Archambault and M. Thomas: Time domain descriptors for rolling-element bearing fault detection, Proceedings of the 20th seminar on machinery vibration, CMVA, Québec (2002).

[4] R.B.W. Heng and M.J.M. Nor: Statistical analysis of sound and vibration signals for monitoring rolling element bearing condition, Applied Acoustics, Vol. 53 (1998) , p.211–226.

DOI: 10.1016/s0003-682x(97)00018-2

[5] M. S. Patil, J. Mathew, P. K. R Kumar: Bearing Signature Analysis as a Medium for Fault Detection: A Review, Journal of Tribology, Vol. 130 (2008)2008, pp.014001-7.

DOI: 10.1115/1.2805445

[6] P. McFadden and J. Smith, Vibration monitoring of rolling element bearings by the high frequency resonance technique —a review, Tribology International, Vol. 17(1984), pp.3-10.

DOI: 10.1016/0301-679x(84)90076-8

[7] N. Tandon and A. Choudhury: A Review of Vibration and Acoustic Measurement Methods for the detection of defects in Rolling Element Bearings, Tribology International, Vol. 32 (1999), pp.469-480.

DOI: 10.1016/s0301-679x(99)00077-8

[8] P. W. Tse, Y. H. Peng and R. Yam: Wavelet analysis and envelope detection for rolling element bearing fault diagnosis-their effectiveness and flexibility, Journal of vibration and acoustics, Vol. 123 (2001), pp.303-310.

DOI: 10.1115/1.1379745

[9] H. Ocak and K. A. Lapora: HMM-based fault detection and diagnosis scheme for rolling element bearing, Journal of vibration and acoustic, Vol. 127 (2005), pp.299-306.

DOI: 10.1115/1.1924636

[10] M. Misiti, Y. Misiti, G. Oppenhein and J. Poggi: Wavelets and their application (ISTE London 2007).

[11] Q. Sun and Y. Tang: Singularity analysis using continuous wavelet transform for bearing fault diagnosis, Mechanical systems and signal processing, Vol. 16 (2002), pp.1025-1041.

DOI: 10.1006/mssp.2002.1474

[12] P. W. Tse, W. Yang and H. Y. Tam: Machine fault diagnosis through an effective exact wavelet analysis, Journal of sound and vibration, Vol. 277 (2004), pp.1005-1024.

DOI: 10.1016/j.jsv.2003.09.031

[13] Y. F. Wang and P. J. Kootsookos: Modeling of low shaft speed bearing faults for condition monitoring, Mechanical systems and signal processing, Vol. 12 (1998), pp.415-426.

DOI: 10.1006/mssp.1997.0149

[14] N. Tondon and A. Choudhary: An analytical model for the prediction of the vibration response of rolling element bearings due to a localized defect, Journal of sound and vibration, Vol. 205 (1997), pp.275-292.

DOI: 10.1006/jsvi.1997.1031