Skip to main content

A new method for detection of rolling bearing faults based on the Local Curve Roughness approach Cover

.blurhash-client-img { display: none !important; }

A new method for detection of rolling bearing faults based on the Local Curve Roughness approach

Polish Maritime Research

Volume 18 (2011): Issue 2 (April 2011)

By: Mehdi Behzad and Abbas Bastami

Open Access

|Jul 2011

Abstract

Detection of rolling bearing faults by vibration analysis is an important part of condition monitoring programs. In this paper a new method for detection of bearing defects based on a new concept of local surface roughness, is proposed. When a defect in the bearing grows then roughness of the defective surface increases and measurement of the roughness can be a good indicator of the bearing defect. In this paper a method of indirectly measuring surface roughness by using vibration signal is introduced. Several attached examples including both numerically simulated signals and actual experimental data show the effectiveness of the new, easy-to-implement method.

References

Zaretski E. V., Poplawski J. V., and Miller C. R.: Rolling Bearing Life Prediction - Past, Present, and Future. NASA, NASA/TM-2000-210529, 2000
Search in Google Scholar
Tandon N. and Choudhury A.: A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings. Tribology International, Vol. 32, No. 32, 1999, pp. 469-480.10.1016/S0301-679X(99)00077-8
Search in Google Scholar
Tandon N. and Nakra B. C.: Vibration and acoustic monitoring techniques for the detection of defects in rolling element bearings - a review. Shock and Vibration Digest, Vol. 24, No. 3, 1992, pp. 3-11.10.1177/058310249202400303
Search in Google Scholar
Taylor J. I.: Identification of bearing defects by spectral analysis. Trans. ASME, Journal of Mechanical Design, Vol. 102, 1980, pp. 199-204.10.1115/1.3254730
Search in Google Scholar
Berry J. E.: How to track rolling element bearing health with vibration signature analysis. S V, Sound and Vibration, Vol. 25, No. 11, 1991, pp. 24-35.
Search in Google Scholar
McFadden P. D. and Smith J. D.: Vibration monitoring of rolling element bearings by the high frequency resonance technique-a review. Tribology International, Vol. 17, No. 1, 1984, pp. 3-10.10.1016/0301-679X(84)90076-8
Search in Google Scholar
Dyer D. and Stewart R. M.: Detection of rolling element bearing damage by statistical vibration analysis. Trans. ASME, Journal of Mechanical Design, Vol. 100, No. 2, 1978, pp. 229-235.10.1115/1.3453905
Search in Google Scholar
Antoni J.: The spectral kurtosis: a useful tool for characterizing non-stationary signals. Mechanical Systems and Signal Processing, Vol. 20, No. 2, 2006, pp. 282-307.10.1016/j.ymssp.2004.09.001
Search in Google Scholar
Bolaers F., Cousinard O., Marconnet P., and Rasolofondraibe L.: Advanced detection of rolling bearing spalling from de-noising vibratory signals. Control Engineering Practice, Vol. 12, No. 2, 2004, pp. 181-190.10.1016/S0967-0661(03)00048-0
Search in Google Scholar
Dron J. P., Bolaers F., and Rasolofondraibe L.: Improvement of the sensitivity of the scalar indicators (crest factor, kurtosis) using a de-noising method by spectral subtraction: application to the detection of defects in ball bearings. Journal of Sound and Vibration, Vol. 270, No. 1-2, 2004, pp. 61-73.10.1016/S0022-460X(03)00483-8
Search in Google Scholar
The shock pulse method for determining the condition of antifriction bearings. SPM Instruments AB, 1980
Search in Google Scholar
Butler D. E.: The shock pulse method for the detection of damaged rolling bearings. NDT International, Vol. 6, No. 2, 1973, pp. 92-95.10.1016/0029-1021(73)90116-3
Search in Google Scholar
McFadden P. D. and Toozhy M. M.: Application of synchronous averaging to vibration monitoring of rolling element bearings. Mechanical Systems and Signal Processing, Vol. 14, No. 6, 2000, pp. 891-906.10.1006/mssp.2000.1290
Search in Google Scholar
Junsheng C., Dejie Y., and Yu Y.: Application of an impulse response wavelet to fault diagnosis of rolling bearings. Mechanical Systems and Signal Processing, Vol. 21, 2007, pp. 920-929.10.1016/j.ymssp.2005.09.014
Search in Google Scholar
Li C. J. and Ma J.: Wavelet Decomposition of Vibrations for Detection of Bearing-Localized Defects. NDT & E International, Vol. 30, 1997, pp. 143-149.10.1016/S0963-8695(96)00052-7
Search in Google Scholar
Mori K., Kasashima N., Yoshika T., and Ueno Y.: Prediction of Spalling on Ball Bearing by Applying the Discrete Wavelet Transform to Vibration Signals. Wear, Vol. 195, 1996, pp. 162-168.10.1016/0043-1648(95)06817-1
Search in Google Scholar
Ocak H., Loparo K. A., and Discenzo F. M.: Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics. Journal of Sound and Vibration, Vol. 302, 2007, pp. 951-961.10.1016/j.jsv.2007.01.001
Search in Google Scholar
Purushotham V., Narayanan S., Suryanarayana and Prasad A. N.: Multi-fault diagnosis of rolling bearing elements using wavelet analysis and hidden Markov model based fault recognition. NDT & E International, Vol. 38, 2005, pp. 654-664.10.1016/j.ndteint.2005.04.003
Search in Google Scholar
Rubini R. and Meneghetti U.: Application of the Envelope and Wavelet Transform Analyses for the Diagnosis of Incipient Faults in Ball Bearings. Mechanical Systems and Signal Processing, Vol. 15, No. 2, 2001, pp. 287-302.10.1006/mssp.2000.1330
Search in Google Scholar
Tse P. W., Peng Y. H., and Yam R.: Wavelet Analysis and Envelope Detection For Rolling Element Bearing Fault Diagnosis - Their Effectiveness and Flexibilities. Trans ASME, Journal of Vibration and Acoustics, Vol. 123, 2001, pp. 303-310.10.1115/1.1379745
Search in Google Scholar
Yang D. M., Stronach A. F., and McConnel P.: Third-Order Spectral Techniques for Diagnosis of Motor Bearing Condition Using Artificial Neural Networks. Mechanical Systems and Signal Processing, Vol. 16, No. 2-3, 2002, pp. 391-411.10.1006/mssp.2001.1469
Search in Google Scholar
Antoni J.: Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions. Journal of Sound and Vibration, Vol. 304, 2007, pp. 497-529.10.1016/j.jsv.2007.02.029
Search in Google Scholar
Du Q. and Yang S: Application of the EMD method in the vibration analysis of ball bearings. Mechanical Systems and Signal Processing, Vol. 21, No. 6, 2007, pp. 2634-2644.10.1016/j.ymssp.2007.01.006
Search in Google Scholar
Junsheng C., Dejie Y., and Yu Y.: A fault diagnosis approach for roller bearings based on EMD method and AR model. Mechanical Systems and Signal Processing, Vol. 20, No. 2, 2006, pp. 350-362.10.1016/j.ymssp.2004.11.002
Search in Google Scholar
Behzad M., Bastami A.R.: Concept of Roughness of Vibration in Rolling Bearings Diagnosis. Proceedings of ISMA Conference, Lueven, 2008
Search in Google Scholar
Sunnersjo C. S.: Varying compliance vibrations of rolling bearings. Journal of Sound and Vibration, Vol. 58, No. 3, 1978, pp. 363-373.10.1016/S0022-460X(78)80044-3
Search in Google Scholar
McFadden P. D. and Smith J. D.: Model for the vibration produced by a single point defect in a rolling element bearing. Journal of Sound and Vibration, Vol. 96, No. 1, 1984, pp. 69-82.10.1016/0022-460X(84)90595-9
Search in Google Scholar
C. M. Harris and A. G. Piersol: Shock and Vibration Handbook. McGraw-Hill, 5^th Ed. 2002
Search in Google Scholar
M. Behzad, A. R. Bastami, D. Mba: A New Model for Estimating Vibrations Generated in the Defective Rolling Element Bearings, ASME Journal of vib & Acoustics, Vol. 133, Aug 2011, pp. 041011-1 to 810.1115/1.4003595
Search in Google Scholar

Articles in this issue

DOI: https://doi.org/10.2478/v10012-011-0011-1 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585

Journal RSS Feed

Language: English

Page range: 44 - 50

Published on: Jul 4, 2011

Published by: Gdansk University of Technology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

rolling bearing,

local curve roughness

Related subjects:

Introductions and overviews,

Engineering, other,

Atmospheric science and climatology,

Life sciences, other

© 2011 Mehdi Behzad, Abbas Bastami, published by Gdansk University of Technology
This work is licensed under the Creative Commons License.

Volume 18 (2011): Issue 2 (April 2011)