Bearing Fault Diagnostics Using the Spectral Pattern Recognition

Pennacchi, P., Borghesani, P., Chatterton, S., & Ricci, R. (2011) Bearing Fault Diagnostics Using the Spectral Pattern Recognition. In Náprstek, Jiří, Horáček, Jaromír, Okrouhlík, Miloslav, Marvalová, Bohdana, Verhulst, Ferdinand, & Sawicki, Jerzy T. (Eds.) Vibration Problems ICOVP 2011. Springer Netherlands, pp. 643-648.

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In the field of diagnostics of rolling element bearings, the development of sophisticated techniques, such as Spectral Kurtosis and 2nd Order Cyclostationarity, extended the capability of expert users to identify not only the presence, but also the location of the damage in the bearing. Most of the signal-analysis methods, as the ones previously mentioned, result in a spectrum-like diagram that presents line frequencies or peaks in the neighbourhood of some theoretical characteristic frequencies, in case of damage. These frequencies depend only on damage position, bearing geometry and rotational speed. The major improvement in this field would be the development of algorithms with high degree of automation. This paper aims at this important objective, by discussing for the first time how these peaks can draw away from the theoretical expected frequencies as a function of different working conditions, i.e. speed, torque and lubrication. After providing a brief description of the peak-patterns associated with each type of damage, this paper shows the typical magnitudes of the deviations from the theoretical expected frequencies. The last part of the study presents some remarks about increasing the reliability of the automatic algorithm. The research is based on experimental data obtained by using artificially damaged bearings installed in a gearbox.

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ID Code: 66504
Item Type: Book Chapter
Additional Information: Springer Proceedings in Physics : The 10th International Conference on Vibration Problems
Keywords: Envelope spectrum, Spectral pattern, automatic diagnostics, rolling element bearings
DOI: 10.1007/978-94-007-2069-5_86
ISBN: 9789400720695
ISSN: 1867-4941
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Dynamics Vibration and Vibration Control (091304)
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 21 Jan 2014 22:57
Last Modified: 24 Oct 2015 16:44

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