Adaptive prognostics for rolling element bearing condition

Rolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. This paper proposes a remaining life adaptation methodology based on mechanistic modeling and parameter tuning. Vibration measurement is used to estimate defect severity by monitoring the signals genera...

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Bibliographic Details
Published in:Mechanical systems and signal processing 1999, Vol.13 (1), p.103-113
Main Authors: Li, Y., Billington, S., Zhang, C., Kurfess, T., Danyluk, S., Liang, S.
Format: Article
Language:English
Subjects:
Adaptive algorithms
Defects
Failure (mechanical)
Forecasting
Rolling
Service life
Vibration measurement
Vibrations (mechanical)
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Summary:Rolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. This paper proposes a remaining life adaptation methodology based on mechanistic modeling and parameter tuning. Vibration measurement is used to estimate defect severity by monitoring the signals generated from rotating bearings. Through a defect propagation model and defect diagnostic model, an adaptive algorithm is developed to fine tune the parameters involved in the propagation model by comparing predicted and measured defect sizes. In this manner, the instantaneous rate of defect propagation can be captured despite defect growth behavior variation. Therefore, a precise estimation of the remaining life can be determined. Simulations and experimental results are presented to illustrate the implementation principles and to verify the applicability of the adaptive prognostic methodology.
ISSN:0888-3270
1096-1216
DOI:10.1006/mssp.1998.0183