Novel method for rolling element bearing health assessment - A tachometer-less synchronously averaged envelope feature extraction technique

Mechanical Systems and Signal Processing

Volumn 29, Issue , 2012, Pages 362-376

  Siegel, David ^a   Al Atat, Hassan ^a   Shauche, Vishwesh ^a   Liao, Linxia ^a   Snyder, John ^b   Lee, Jay ^a  

^a UNIVERSITY OF CINCINNATI   (United States)

^b Techsolve   (United States)

Author keywords

Bearing health assessment; Envelope analysis; Hilbert transform; Synchronous averaging

Indexed keywords

AVERAGE METHOD; BEARING DAMAGE; BEARING DEFECT; BEARING FAILURES; BEARING FAULT; CLASSIFICATION ALGORITHM; COST EFFECTIVE; EMPIRICAL MODE DECOMPOSITION; ENVELOPE ANALYSIS; ENVELOPE FEATURE; ENVELOPE METHOD; ENVELOPE SPECTRA; FAULT FREQUENCY; FEATURE EXTRACTION TECHNIQUES; FREQUENCY CONTENTS; HEALTH ASSESSMENTS; HIGH FREQUENCY; HILBERT TRANSFORM; MAINTENANCE DECISIONS; MONOTONIC TREND; NARROW-BAND PASS FILTERS; NARROWBAND SIGNAL; OUTER RACES; PROCESSING METHOD; RESEARCH TOPICS; ROLLING ELEMENT BEARING; ROTATIONAL SHAFTS; ROTATIONAL SPEED; RUN TO FAILURES; SYNCHRONOUS AVERAGING; VIBRATION DATA;

DEFECTS; DEGRADATION; FEATURE EXTRACTION; HEALTH; RATING; SIGNAL DETECTION; TACHOMETERS;

DAMAGE DETECTION;

EID: 84862824347     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2012.01.003     Document Type: Conference Paper

References (27)

1. A.K.S. Jardine, D. Lin, and D. Banjevic A review on machinery diagnostics and prognostics implementing condition-based maintenance Mech. Syst. Signal Process. 20 7 2006 1483 1510
2. A. Heng, S. Zhang, A.C.C Tan, and J. Mathew Rotating machinery prognostics: state of the art, challenges and opportunities Mech. Syst. Signal Process. 23 3 2008 724 739
3. Qiu, H., Luo, H., Eklund, N., On-board aircraft engine bearing prognostics: enveloping or fft analysis?, in: Proceedings of the ASME 2009 International Design Engineering Technical Conferences & Computers Information in Engineering, 2009.
4. Z.K. Peng, and F.L. Chu Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography Mech. Syst. Signal Process. 18 2 2004 199 221
5. Z.K. Peng, P.W. Tse, and F.L. Chu A comparison study of improved Hilbert-Huang transform and wavelet transform: application to fault diagnosis for rolling bearing Mech. Syst. Signal Process. 19 5 2005 974 988 (Pubitemid 40612481)
6. Huang, N.E., Shen, Z., Long, S.R., Wu, M.L.C., Shih, H.H., Zheng, Q.N., Yen, N.C., Tung, C.C., Liu, H.H., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proc. R. Soc. Long Ser. A-Math. Phys. Eng. Sci. 454 (1998) 903995. (Pubitemid 128733183)
7. Khatri, H., Ranney, K., Tom, K., del Rosario, R., New features for diagnosis and prognosis of systems based on empirical mode decomposition, in: Proceedings of 2008 International Conference on Prognostics and Health Management, 2008.
8. F. Wu, and L. Qu An improved method for restraining the end effect in empirical mode decomposition and its applications to the fault diagnosis of large rotating machinery J. Sound Vib. 314 2008 586 602
9. P. Vecer, M. Kreidl, and R. Smid Condition indicators for gearbox monitoring systems Acta Polytech. 45 6 2005 35 43
10. P.D. McFadden, and M.M. Toozhy Application of synchronous averaging to vibration monitoring of rolling element bearings Mech. Syst. Signal Process. 14 6 2000 891 906 (Pubitemid 32076534)
11. Sawalhi, N., Diagnostics, prognostics and fault simulation for rolling element bearings, PhD Thesis, University of New South Wales, 2007.
12. B. Li, M. Chow, Y. Tipsuwan, and J. Hung Neural-network-based motor rolling bearing fault diagnosis IEEE Trans. Ind. Electron. 47 5 2000 1060 1069
13. Q. Du, and S. Yang Application of the EMD method in the vibration analysis of ball bearings Mech. Syst. Signal Process. 21 6 2007 2634 2644 (Pubitemid 46829763)
14. Huang, N.E., Wu, Z., Ensemble empirical mode decomposition: a noise-assisted data analysis method, COLA Technical Report 193, Center for Ocean-Land-Atmosphere Studies, 2005.
15. Q. Chen, N. Huang, S. Riemenschneider, and Y. Xu A B-spline approach for empirical mode decompositions Adv. Comput. Math. 24 2006 171 195 (Pubitemid 43563918)
16. G. Rilling, and P. Flandrin One or two frequencies? The empirical mode decomposition answers IEEE Trans. Signal Process. 56 1 2008 85 95
17. M. Feldman Analytical basics of the EMD: two harmonics decomposition Mech. Syst. Signal Process. 23 7 2009 2059 2071
18. R.B. Randall, and J. Antoni Rolling element bearing diagnosticsa tutorial Mech. Syst. Signal Process. 25 2 2011 485 520
19. J. Antoni The spectral kurtosis: a useful tool for characterizing nonstationary signals Mech. Syst. Signal Process. 20 2 2006 282 307 (Pubitemid 41606170)
20. J. Antoni, and R.B. Randall The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines Mech. Syst. Signal Process. 20 2 2006 308 331 (Pubitemid 41606171)
21. J. Antoni Fast computation of the kurtogram for the detection of transient faults Mech. Syst. Signal Process. 21 1 2006 108 124
22. Dyer, D., Stewart, R.M., Detection of rolling element bearing damage by statistical vibration analysis, ASME Paper, 26-30 September, 1997.
23. Antoni, J., webpage; 〈http://www.utc.fr/-antoni〉.
24. M. Feldman Hilbert transform in vibration analysis Mech. Syst. Signal Process. 25 3 2011 735 802
25. B. Boashas Estimating and interpreting the instantaneous frequency of a signal-Part 1: Fundamentals Proc. IEEE 80 4 1992 520 539
26. H. Luo, H. Qiu, G. Ghanime, M. Hirz, and G. Van der Merwe Synthesized synchronous sampling technique for differential bearing damage detection J. Eng. Gas Turbines Power 132 7 2010
27. Siegel, D., Evaluation of health assessment techniques for rotating machinery, Master Thesis, University of Cincinnati, 2009.