A combined spectral subtraction and wavelet de-noising method for bearing fault diagnosis

Proceedings of the American Control Conference

Volumn , Issue , 2007, Pages 2533-2538

  Bozchalooi, I Soltani ^a   Liang, Ming ^a  

^a UNIVERSITY OF OTTAWA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRIC FAULT CURRENTS; FILTRATION; MAGNETIC FILTERS; WAVE FILTERS;

APPLIED (CO); ARITHMETIC MEAN (AM); BAND PASS FILTERING; BEARING FAULTS; CENTER FREQUENCY (CF); DE-NOISING; DENOISING METHODS; EXPERIMENTAL DATA; FAULTY BEARINGS; FREQUENCY CONTENTS; GABOR WAVELETS; GEOMETRIC MEAN (MG); IN-BAND NOISE; SMOOTHNESS INDEX (SI); SPECTRAL SUBTRACTIONS; VIBRATION SIGNALS; WAVELET COEFFICIENTS; WAVELET DE-NOISING; WAVELET FILTERING;

BEARINGS (STRUCTURAL);

EID: 46449125921     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACC.2007.4282467     Document Type: Conference Paper

References (15)

1. P. D. McFadden and J. D. Smith, "Model for the vibration produced by a single point defect in a rolling element bearing," Journal of Sound and Vibration, vol. 96, no. 1, pp.69-82, 1984.
2. J. Lin and Q. Liangsheng, "Feature extraction based on morlet wavelet and its application in mechanical fault diagnosis," Journal of Sound and Vibration, vol. 234, no. 1, pp.135-148, 2000.
3. H. Qiu, J. Lee, J. Lin, and G. Yu, "Wavelet filter-based weak signature detection method and its application on rolling element bearing prognosis," Journal of Sound and Vibration, vol.289, no. 4-5, pp. 1066-1090, 2006.
4. H. Qiu J. Lee, J. Lin, and G. Yu, "Robust performance degradation assessment methods for enhanced rolling element bearing prognostics," Advanced Engineering Informatics, vol. 17, no. 3-4, pp.127-140, 2003.
5. J. Lin and M. J. Zuo, "Gearbox fault, diagnosis using adaptive wavelet filter," Mechanical Systems and Signal Processing, vol. 17, no. 6, pp. 1259-1269, 2003.
6. N. G. Nikolaou and I. A. Antoniadis, "Demodulation of vibration signals generated by defects in rolling element bearings using complex shifted morlet wavelets," Mechanical Systems and Signal Processing, vol.16, no. 4, pp.677-694, 2002.
7. I. S. Bozchalooi and M. Liang, "A Smoothness Index Guided Approach to Wavelet Parameter Selection in Signal De-Noising and Fault Detection," submitted for publication.
8. S. Mallat, A wavelet tour of signal processing. San Diego: Academic Press, 1998.
9. R. M. Rao and A.S. Bopardikar, Wavelet transforms: Introduction to theory and application. Reading, MA: Addison Wesley, 1998, ch. 1.
10. M. Abramowitz and A. I. Stegun, Handbook of mathematical functions with formulas, graphs and mathematical tables. New York: Dover Publications, 1972, pp. 10-11.
11. S. M. Kay, "The effect of noise on the autoregressive spectral estimator," IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 27, no. 5, pp.478-485, 1979.
12. Bearing data center, seeded fault test data. Available: http://www.eecs.cwru.edu/laboratory/bearing
13. J. S. Lim and A. V. Oppenheim, "Enhancement and bandwidth compression of noisy speech," Proceedings of the IEEE, vol. 67, no. 12, pp.1586-1604, 1979.
14. J. P. Dron, F. Bolaers, Rasolofondraibe, "Improvement of the sensitivity of the scalar indicators (crest factor, kurtosis) using a denoising method by spectral subtraction: application to the detection of defects in ball bearings," Journal of Sound and Vibration, vol. 270, no. 1-2, pp.61-73, 2004.
15. P. D. McFadden and J. D. Smith, "Vibration monitoring of rolling element bearing by the high-frequency resonance technique- a review," Tribology International, vol. 17, no. 1, pp.3-10, 1984.