An algorithm to diagnose ball bearing faults in servomotors running arbitrary motion profiles

Mechanical Systems and Signal Processing

Volumn 27, Issue 1, 2012, Pages 667-682

  Cocconcelli, Marco ^a   Bassi, Luca ^b,c   Secchi, Cristian ^a   Fantuzzi, Cesare ^a   Rubini, Riccardo ^a  

^a UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

^b Tetra Pak Carton Ambient   (Italy)

^c EUROPEAN PATENT OFFICE   (Netherlands)

Author keywords

Ball bearings; Envelope analysis; Order tracking; Prognostics

Indexed keywords

BEARING FAULT; CLASSICAL METHODS; CONDITION-BASED MONITORING; ENVELOPE ANALYSIS; FAULT FREQUENCY; MOTION INVERSION; MOTION PROFILE; NORMAL MODES; ORDER TRACKING; PROGNOSTICS; THEORETICAL POINTS;

ALGORITHMS; INDUSTRIAL APPLICATIONS; SERVOMOTORS;

BALL BEARINGS;

EID: 82255162678     PISSN: 08883270     EISSN: 10961216     Source Type: Journal    
DOI: 10.1016/j.ymssp.2011.09.003     Document Type: Article

References (39)

1. Load rating and fatigue life of ball bearings, ANSI/AFBMA Standard 9-1978, 1978.
2. J. Taylor, D. Kirkland, The Bearing Analysis Handbook: A Practical Guide for Solving Vibration Problems in Bearings, Vibration Consultants, 2004.
3. T. Harris Rolling Bearing Analysis 2001 Wiley and Sons
4. M. Cocconcelli, and R. Rubini Relationship between vibration energy and wear condition of ball bearings based on reyes hypothesis Proceedings of the Sixteenth International Congress on Sound and Vibration 2009
5. P. Vlok, M. Wnek, and M. Zygmunt Utilising statistical residual life estimates of bearings to quantify the influence of preventive maintenance actions Mech. Syst. Signal Process. 18 2004 833 847
6. N. Gebraeel Sensory-updated residual life distributions for components with exponential degradation patterns IEEE Trans. Autom. Sci. Eng. 3 4 2006 382 393 (Pubitemid 44574332)
7. N. Gebraeel, A. Elwany, and J. Pan Residual life predictions in the absence of prior degradation knowledge IEEE Trans. Reliab. 58 1 2009 106 117
8. P. McFadden, and J. Smith Vibration monitoring of rolling element bearings by the high-frequency resonance technique - a review Tribol. Int. 17 1 1984 3 10 (Pubitemid 14561780)
9. P. McFadden, and M. Toozhy Application of synchronous averaging to vibration monitoring of rolling element bearings Mech. Syst. Signal Process. 14 6 2000 891 906 (Pubitemid 32076534)
10. G. Giuliani, R. Rubini, and A. Maggiore Ball bearing diagnostics using neural networks Proceedings of the Third International Conference on Acoustical and Vibratory Surveillance Methods and Diagnostics Techniques 1998
11. Y. Pan, J. Chen, and X. Lee Spectral entropy: a complementary index for rolling element bearing performance degradation assessment Proceedings of the Institution of Mechanical Engineers 2009
12. J. Antoni Cyclic spectral analysis of rolling-element bearing signals: facts and fictions J. Sound Vib. 304 6 2007 497 529 (Pubitemid 46764722)
13. J. Antoni, and R. 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)
14. C. Junsheng, Y. Dejie, and Y. Yu A fault diagnosis approach for roller bearings based on EMD method and AR model Mech. Syst. Signal Process. 20 2 2006 350 362 (Pubitemid 41606173)
15. D. Yang, A. Stronach, and P. MacConnell Third-order spectral techniques for the diagnosis of motor bearing condition using artificial neural networks Mech. Syst. Signal Process. 16 23 2002 391 411 (Pubitemid 40000348)
16. R. Rubini, and U. Meneghetti Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings Mech. Syst. Signal Process. 15 2 2001 287 302 (Pubitemid 32409308)
17. K. Al-Raheem, A. Roy, K. Ramachandran, D. Harrison, and S. Grainger Rolling element bearing fault diagnosis using Laplace-wavelet envelope power spectrum EURASIP J. Adv. Signal Process. 1 2007 70
18. D. Yu, J. Cheng, and Y. Yang Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings Mech. Syst. Signal Process. 19 2 2005 259 270
19. H. Li, H. Zheng, and L. Tang Faults monitoring and diagnosis of ball bearing based on HilbertHuang transformation Key Eng. Mater. 291292 2005 649 654 (Pubitemid 46806036)
20. H. Li, and Y. Zhang Bearing faults diagnosis based on EMD and WignerVille distribution Proceedings of the Sixth World Congress on Intelligent Control and Automation 2006
21. W. Martin, and P. Flandrin WignerVille spectral analysis of nonstationary processes IEEE Trans. Acoust. Speech Signal Process. 33 6 1985 1461 1470 (Pubitemid 16524952)
22. B. Kim, S. Lee, J. Ni, and J. Song A comparative study on the vibration signal-based damage detection for rotor-bearing system in speed-up process: the feature extraction approach Key Eng. Mater. 321323 2006 1253 1256 (Pubitemid 44517989)
23. M. Cocconcelli, R. Rubini, Introduction to a simply and fast algorithm for variable speed bearing diagnostics, in: Seconda giornata di studio Ettore Funaioli, 2009.
24. M. Cocconcelli, C. Secchi, R. Rubini, C. Fantuzzi, and L. Bassi Comparison between time-frequency techniques to predict ball bearing faults in drives executing arbitrary motion profiles Proceedings of ASME International Mechanical Engineering Congress & Exposition 2008
25. W. Bartelmus, and R. Zimroz A new feature for monitoring the condition of gearboxes in non-stationary operating conditions Mech. Syst. Signal Process. 23 5 2009 1528 1534
26. C. Stander, P. Heyns, and W. Schoombie Using vibration monitoring for local fault detection on gears operating under fluctuating load conditions Mech. Syst. Signal Process. 16 6 2002 1005 1024 (Pubitemid 35474417)
27. C. Stander, and P. Heyns Instantaneous angular speed monitoring of gearboxes under non-cyclic stationary load conditions Mech. Syst. Signal Process. 19 2005 817 835 (Pubitemid 40556436)
28. N. Baydar, and A. Ball Detection of gear deterioration under varying load conditions by using the instantaneous power spectrum Mech. Syst. Signal Process. 14 2000 907 921 (Pubitemid 32076535)
29. Y. Zhan, Y. Makis, and A. Jardine Adaptive state detection of gearboxes under varying load conditions based on parametric modelling Mech. Syst. Signal Process. 20 1 2004 188 221 (Pubitemid 41566169)
30. X. Wang, V. Makis, and M. Yang A wavelet approach to fault diagnosis of a gearbox under varying load conditions J. Sound Vib. 329 9 2010 1570 1585
31. R. Potter A new order tracking method for rotating machinery Sound Vib. 24 1990 30 34
32. K. Fyfe, and E. Munck Analysis of computed order tracking Mech. Syst. Signal Process. 11 2 1997 187 205
33. M. Cocconcelli, C. Secchi, R. Rubini, C. Fantuzzi, and L. Bassi Predictive maintenance of ball bearings for machines rotating with arbitrary velocity profiles Proceedings of the International Conference on Noise and Vibration Engineering 2008
34. R.B. Randall, J. Antoni, and S. Chobsaaard The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals Mech. Syst. Signal Process. 15 5 2001 945 962 (Pubitemid 33112620)
35. J. Antoni, and R.B. Randall Unsupervised noise cancellation for vibration signals: part I - evaluation of adaptive algorithms Mech. Syst. Signal Process. 18 2004 89 101
36. J. Antoni, and R.B. Randall Unsupervised noise cancellation for vibration signals: part II - a novel frequency-domain algorithm Mech. Syst. Signal Process. 18 2004 103 117
37. A. 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
38. C. Harris, and A. Persol Harris Shock and Vibration Handbook 2001 McGraw Hill
39. P.E. Luft, and T.I. Laakso Adaptive control of sampling rate using a local time-domain sampling theorem International Symposium on Circuits and Systems vol. 3 1994 IEEE 145 148