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2011 | 18 | 2 |
Tytuł artykułu

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

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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
Słowa kluczowe
Wydawca
-
Rocznik
Tom
18
Numer
2
Opis fizyczny
p.44-50,fig.,ref.
Twórcy
autor
  • Mechanical Engineering Department, Sharif University of Technology, 11155-9567, Azadi Avenue, Teheran, Iran
autor
  • Mechanical Engineering Department, Sharif University of Technology, 11155-9567, Azadi Avenue, Teheran, Iran
Bibliografia
  • 1. Zaretski E. V., Poplawski J. V., and Miller C. R.: Rolling Bearing Life Prediction - Past, Present, and Future. NASA, NASA/TM-2000-210529, 2000
  • 2. 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.
  • 3. 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.
  • 4. Taylor J. I.: Identification of bearing defects by spectral analysis. Trans. ASME, Journal of Mechanical Design, Vol. 102, 1980, pp. 199-204.
  • 5. 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.
  • 6. 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.
  • 7. 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.
  • 8. 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.
  • 9. 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. 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.
  • 11. The shock pulse method for determining the condition of antifriction bearings. SPM Instruments AB, 1980
  • 12. Butler D. E.: The shock pulse method for the detection of damaged rolling bearings. NDT International, Vol. 6, No. 2, 1973, pp. 92-95.
  • 13. 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.
  • 14. 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.
  • 15. 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.
  • 16. 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. 162168.
  • 17. 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.
  • 18. 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.
  • 19. 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.
  • 20. 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.
  • 21. 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.
  • 22. Antoni J.: Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions. Journal of Sound and Vibration, Vol. 304, 2007, pp. 497-529.
  • 23. 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.
  • 24. 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.
  • 25. Behzad M., Bastami A.R.: Concept of Roughness of Vibration in Rolling Bearings Diagnosis. Proceedings of ISMA Conference, Lueven, 2008
  • 26. Sunnersjo C. S.: Varying compliance vibrations of rolling bearings. Journal of Sound and Vibration, Vol. 58, No. 3, 1978, pp. 363-373.
  • 27. 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.
  • 28. C. M. Harris and A. G. Piersol: Shock and Vibration Handbook. McGraw-Hill, 5th Ed. 2002
  • 29. 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 8
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.agro-c74251d6-f8c6-4ae1-9775-f9dec6d30b45
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