Bearing fault diagnosis based on the dimension-temporal information

Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology

Volumn 225, Issue 8, 2011, Pages 806-813

  Zhang, D D ^a  

^a BEIHANG UNIVERSITY   (China)

Author keywords

Fault diagnosis; Trending analysis; Vibration analysis

Indexed keywords

BEARING DAMAGE; BEARING FAULT; BEARING FAULT DIAGNOSIS; ENERGY INDEXES; HEALTH ASSESSMENTS; MOTOR BEARINGS; TEMPORAL INFORMATION; TRENDING ANALYSIS; VIBRATION PATTERN; VIBRATION SIGNAL;

BEARINGS (STRUCTURAL); DAMAGE DETECTION; DYNAMIC RESPONSE; FAILURE ANALYSIS;

VIBRATION ANALYSIS;

EID: 80052801223     PISSN: 13506501     EISSN: 2041305X     Source Type: Journal    
DOI: 10.1177/1350650111410254     Document Type: Conference Paper

References (21)

1. Howard, I. A review of rolling element bearing vibration - detection, diagnosis and prognosis. Technical Report DSTO-RR-0013, Defence Science and Technology Organisation, Australia, 1994.
2. Dyer, D. and Stewart, R. M. Detection of rolling element bearing damage by statistical vibration analysis. ASME J. Mech. Des., 1978, 100(2), 229-235.
3. Khan, A. F. Condition monitoring of rolling element bearings: a comparative study of vibration based techniques. Ph.D. Thesis, University of Nottingham, 1991.
4. Lybeck, N., Marble, S., and Morton, B. Validating prognostic algorithms: a case study using comprehensive bearing fault data. In Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, USA, 3-10 March 2007, pp. 1-9.
5. McFadden, P. D. and Smith, J. D. Model for the vibration produced by a single point defect in a rolling element bearing. J. Sound Vib., 1984, 96(1a), 69-82. (Pubitemid 15421328)
6. McFadden, P. D. and Smith, J. D. Model for the vibration produced by multiple point defects in a rolling element bearing. J. Sound Vib., 1985, 98(2), 263-273.
7. Su, Y. T. and Lin, S. J. On initial fault detection of a tapered roller bearing: frequency domain analysis. J. Sound Vib., 1992, 155(1), 75-84.
8. Su, Y. T. and Sheen, Y. T. On the detectability of roller bearing damage by frequency analysis. Proc. IMechE, Part C: J. Mechanical Engineering Science, 1993, 207, 23-32.
9. McFadden, P. D. and Smith, J. D. Vibration monitoring of rolling element bearings by the high frequency resonance technique - a review. Tribol. Int., 1984, 17, 3-10. (Pubitemid 14561780)
10. Kallappa, P., Byington, C., Kalgren, P., DeChristopher, M., and Amin, S. High frequency incipient fault detection for engine bearing components. In Proceedings of the ASME Turbo Expo 2005 on Power for land, sea and air, Nevada, USA, 6-9 June 2005, pp. 1-15.
11. Watson, M., Begin, M., Amin, S., Sheldon, J., Lee, H., and Byington, C. A comprehensive high frequency vibration monitoring system for incipient fault detection and isolation of gears, bearings and shafts/ couplings in turbine engines and accessories. In Proceedings of the ASME Turbo Expo 2007 on Power for land, sea and air, Montreal, Canada, 14-17 May 2007, pp. 1-10.
12. Byington, C. S., Orsagh, R., Kallappa, P., Sheldon, J., DeChristopher, M., and Amin, S. Recent case studies in bearing fault detection and prognosis. In Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, USA, 4-11 March 2006, pp. 1-8.
13. Sun, Q. and Ying, T. Singularity detection using continuous wavelet transform for bearing fault diagnosis. Mech. Syst. Sig. Process., 2002, 16(6), 1025-1041. (Pubitemid 35466623)
14. Sun, Q., Chen, P., Zhang, D. J., and Xi, F. F. Pattern recognition for automatic machinery fault diagnosis. ASME J. Vib. Acoust., 2004, 126(2), 307-316.
15. Dempsey, P. J., Certo, J. M., Handschuh, R. F., and Dimofte, F. Hybrid bearing prognostic test rig. Technical Report NASA/TM-2005-213597, Glenn Research Center, 2005.
16. Roemer, M., Kacprzynski, G., and Orsagh, R. Assessment of data and knowledge fusion strategies for prognostics and health management. In Proceedings of the IEEE Aerospace Conference Big Sky, Montana, 10-17 March 2001, vol. 6, pp. 2979-2988.
17. Melek, W. W., Lu, Z., Kapps, A., and Fraser, W. D. Comparison of trend detection algorithms in the analysis of physiological time-series data. IEEE Trans. Biomed. Eng., 2005, 52(4), 639-651. (Pubitemid 40477174)
18. Hope, E., Lewis, C. D., Perry, I. R., and Gamble, A. Computed trend analysis in automated patient monitoring systems. Br. J. Anaesth., 1973, 45(5), 440-448.
19. Kennedy, R. R. A modified Trigg's tracking variable as an 'advisory' alarm during anaesthesia. Int. J. Clin. Monit. Comput., 1995, 12, 197-204. (Pubitemid 26037865)
20. Friedman, N., Geiger, D., and Goldszmidt, M. Bayesian network classifiers. Mach. Learn., 1997, 29, 131-163. (Pubitemid 127510036)
21. Bearing Data Center Case Western Reserve University, available from http://www.eecs.case. edu/laboratory/bearing/.