Comparison of advanced signal-processing methods for roller bearing faults detection

Metrology and Measurement Systems

Volumn 19, Issue 4, 2012, Pages 715-726

  Urbanek, Jacek ^a   Barszcz, Tomasz ^a   Uhl, Tadeusz ^a  

^a AGH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Poland)

Author keywords

Condition monitoring; Fault detection; Rolling element bearings; Wind turbine

Indexed keywords

CONDITION MONITORING; FAULT DETECTION; SIGNAL PROCESSING; SPECTRUM ANALYSIS; WIND TURBINES;

ADVANCED SIGNAL PROCESSING; CONFIGURATION PARAMETERS; CYCLOSTATIONARITY; ENVELOPE ANALYSIS; INDUSTRIAL PRACTICES; OPERATIONAL CONDITIONS; ROLLER BEARING FAULT; ROLLING ELEMENT BEARING;

ROLLER BEARINGS;

EID: 84872173926     PISSN: 08608229     EISSN: None     Source Type: Journal    
DOI: 10.2478/v10178-012-0063-2     Document Type: Article

References (20)

1. Zoltowski, B., Cempel, C. (2004). Engineering of Machinery Diagnostics PTDT ITE PIB Radom. Warszawa, Bydgoszcz, Radom. (in Polish)
2. Klein, U., (2003). Schwingungsdiagnostische Beurteilung von Maschinen und Anlagen (Vibrodiagnostic assessment of machines and devices). Stahleisen Verlag, Duesseldorf.
3. Taylor, T. (2000). The bearing analysis handbook. Vibration Consultants Inc.
4. Antoni, J. (2009). Cyclostationarity by examples. Mechanical Systems and Signal Processing, 23, 987-1036.
5. Randall, R.B., Antoni, J. (2011) Rolling element bearing diagnostics - A. tutorial. Mechanical Systems and Signal Processing, 25, 485-520.
6. Urbanek, J., Antoni, J., Barszcz, T. (2012). Detection of signal component modulations using modulation intensity distribution. Mechanical Systems and Signal Processing, 28, 399-413.
7. Davis, F.B. (1996). Advanced vibration analysis techniques for fault detection and diagnosis in geared transmission systems. PhD thesis. Swinburn University of Technology, Australia.
8. Urbanek, J., Barszcz, T., Zimroz, R., Antoni, J. (2012). Application of averaged instantaneous power spectrum for diagnostics of machinery operating under non-stationary operational conditions. Measurement 45, 1782-1791.
9. Barszcz, T. (2009). Selection of diagnostic algorithms for wind turbines. Diagnostyka, 50, 7-12.
10. Zimroz, R., Barszcz, T., Urbanek, J., Bartelmus, W., Millioz, F., Martin, N. (2011). Measurement Of Instantaneous Shaft Speed By Advanced Vibration Signal Processing & Application To Wind Turbine Gearbox. Metrol. Meas. Syst.,18(4), 701-712.
11. Urbanek, J., Barszcz, T., Sawalhi, N., Randall, R.B. (2011). Comparison of amplitude based and phase based methods for speed tracking in application to wind turbines. Metrol. Meas.Syst., 18(2), 295-304.
12. Gellermann, T. (2003). Requirements for Condition Monitoring Systems for Wind Turbines, AZT Expertentage,. Allianz
13. Hau, E. (2006). Wind Turbines. Springer, Berlin.
14. Zimroz, R, (2009). Some remarks on local damage diagnosis in presence of multi-faults and non-stationary operation. The Sixth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Dublin, Ireland, The British Institute of Non-Destructive Testing, US Society for Machinery Failure Prevention Technology, 33-44.
15. Ebner, R., Gruber, P., Ecker, W., Kolednik, O., Krobath, M., Jesner, G. (2010). Fatigue damage mechanisms and damage evolution near cyclically loaded edges. Bull. Pol. Acad. Sci.-Tech. Sci., 58(2).
16. Antoni, J. (2007). Fast computation of the kurtogram for the detection of transient faults. Mechanical Systems and Signal Processing, 21, 108-124.
17. Antoni, J. (2006). The spectral kurtosis: a useful tool for characterising non-stationary signals. Mechanical Systems and Signal Processing, 20, 282-307.
18. Antoni, J., Randall, R.B. (2006). The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mechanical Systems and Signal Processing, 20, 308-331.
19. Halang, W.A., Śnieżek, M. (2010). A safe programmable electronic system. Bull. Pol. Acad. Sci.-Tech. Sci., 58(3).
20. Slowik, A. (2011). Application of evolutionary algorithm to design minimal phase digital filters with nonstandard amplitude characteristics and finite bit word length. Bull. Pol. Acad. Sci.-Tech. Sci., 59(2).