Vibration Analyses of the Bearing Using the Time Frequency Domain Technique

Article Preview

Abstract:

This work employs the wavelet transform for reading the fault diagnosis in a rotor-bearing system. Initiating with literature review with some relevant studies of bearing fault and the signal processing techniques used followed by the theory of wavelet transform. A bearing test rig is shown which is used for implementing wavelet transform. A faulty bearing vibration signal is measured from the test rig; thereafter the fast Fourier transform is plotted to show the critical frequencies, bearing characteristics frequency and its harmonics. A scalogram showing the energy levels of signal is plotted as result. Faulty signal is analyzed using wavelet transform.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

2091-2096

Citation:

Online since:

July 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] P.D. McFadden, J.D. Smith, A signal processing technique for detecting local defects in a gear from the signal average of the vibration, Proceedings of the Institution of Mechanical Engineers, 199 (C4) (1985), p.287–292.

DOI: 10.1243/pime_proc_1985_199_125_02

Google Scholar

[2] F.K. Choy, S. Huang, J.J. Zakrajsek, R.F. Handschuh, D.P. Townsend, Vibration signature analysis of a faulted gear transmission system, Journal of Propulsion and Power 12(2) (1996), pp.289-295.

DOI: 10.2514/3.24026

Google Scholar

[3] W.J. Wang, P.D. McFadden, Application of wavelets to bearing vibration signal for fault detection, journal of sound and vibration, 192 (5) (1996), pp.927-939.

DOI: 10.1006/jsvi.1996.0226

Google Scholar

[4] C. K Sung , H. M Tai, C. W Chen, Locating defects of a gear system by the technique of wavelet transform, Mechanism and Machine Theory, 35(8) (2000), pp. -1169-1182.

DOI: 10.1016/s0094-114x(99)00045-2

Google Scholar

[5] M.A. Jafarizadeh, R. Hassannejad, M.M. Ettefagh, S. Chitsaz, Asynchronous input gear damage diagnosis using time averaging and wavelet filtering, Mechanical Systems and Signal Processing, 22 (2008), p.172–201.

DOI: 10.1016/j.ymssp.2007.06.006

Google Scholar

[6] D. Ho, R.B. Randall, Optimization of bearing diagnostic techniques using simulated and actual bearing fault signals, Mechanical Systems and Signal Processing 14 (2000) 763–788.

DOI: 10.1006/mssp.2000.1304

Google Scholar

[7] H Qiu, J Lee, J Lin, G Yu, Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics, Journal of Sound and Vibration 289 (2006) 1066–1090.

DOI: 10.1016/j.jsv.2005.03.007

Google Scholar

[8] R.B. Randall, Frequency Analysis, third ed. Bruel&Kjaer (1987).

Google Scholar

[9] R.L. Eshleman, Comments on rolling element bearing analysis, Vibrations 13 (2) (1997) 11–17.

Google Scholar

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

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

Google Scholar

[11] R. Yan, R. X. Gao, X. Chen, Wavelets for fault diagnosis of rotary machines: A review with applications, Signal Processing, 96 (A) (2014), pp.1-15.

DOI: 10.1016/j.sigpro.2013.04.015

Google Scholar

[12] M. Stéphane, A Wavelet Tour of Signal Processing The Sparse Way, (Third Edition).

Google Scholar

[13] N. Saravanan, K.I. Ramachandran, A case study on classification of features by fast single-shot multiclass PSVM using Morlet wavelet for fault diagnosis of spur bevel gear box, Expert Systems with Applications, 36 (2009), pp.10854-10862.

DOI: 10.1016/j.eswa.2009.01.053

Google Scholar

[14] Y. Lei, J. Lin, M. J. Zuo, Z. He, Condition monitoring and fault diagnosis of planetary gearboxes: A review, Measurement, 48 (2014), p.292–305.

DOI: 10.1016/j.measurement.2013.11.012

Google Scholar