Assessment of the remaining useful life of a rolling-element bearing is a key element in rotating machines prognostics. Evaluation of the bearing remaining useful life (RUL) requires diagnosis of the fault existence, estimation of its size and estimation of the time interval until it reaches a critical size. A concept for bearing RUL estimation is proposed. The main insights which led to the concept development are reviewed. The study focuses on estimation of spall size located in one of the bearing races. A new approach for estimation of spall size in bearing races is developed based on physical insights obtained from results of a general bearing dynamic model. Analytical modeling of the interaction between the spall and the rolling element enables the development of an autonomous generic method for spall size estimation. In this paper the principles for spall size estimation are described. The new method was applied to experimental data including different spall sizes on inner and outer races. The estimation shows satisfactory results with errors up to 20%.
How to Cite
bearing fault diagnosis, Vibration
Epps, I. (1991). An investigation into vibrations excited by discrete faults in rolling element bearings (Unpublished doctoral dissertation). University of Canterbury. Mechanical Engineering. Gazizulin, D., Klein, R. & Bortman, J. (2017). Towards a Physics Based foundation for the estimation of bearings RUL, Proceedings of Asia Pacific Conference of the Prognostics and Health Management Society, Jeju, Korea, July, 2017.
Heng, A., Zhang, S., Tan, A. C., & Mathew, J. (2009). Rotating machinery prognostics: State of the art, challenges and opportunities. Mechanical systems and signal processing, 23(3), 724-739. Kogan, G., Bortman, J., & Klein, R. (2017). A new model for spall-rolling-element interaction. Nonlinear Dynamics, 87(1), 219-236.
Kogan, G., Klein, R., Kushnirsky, A., & Bortman, J. (2015). Toward a 3d dynamic model of a faulty duplex ball bearing. Mechanical Systems and Signal Processing, 54, 243–258. Kogan, G., Madar, E., Klein, R & Bortman, J. (2016). Spall size estimation in bearing races based on vibration analysis. Annual conference of the European Conference of the Prognostics and Health Management Society, Bilbao, Spain, July 2016.
L. Cui, N. Wu, C. Ma, H. Wang, Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary, Mech. Syst. Signal Process. 68 (2016) 34–43.
Madar, E., Kogan, G., Klein, R & Bortman, J. (2016). Estimation of spall size in bearing inner race based on vibration analysis. The Thirteenth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Paris, France, October, 2016. Madar, E., Kogan, G., Klein, R. & Bortman, J. (2017). An analytical model for rolling-element-spall interaction in bearing inner race. Proceedings of First World Congress on Condition Monitoring Conference, London, England, June, 2017.
Mendelovich, M., Sanders, Y., Kogan, G., Battat, M., Klein, R., & Bortman, J. (2014). Characterization of fault size in bearings. Annual conference of the Prognostics and Health Management Society, Fort Worth, Texas, September 2014.
N. Sawalhi, R. Randall, Vibration response of spalled rolling element bearings: Observations, simulations and signal processing techniques to track the spall size, Mech. Syst. Signal Process. 25 (3) (2011) 846–870.
S. Zhao, L. Liang, G. Xu, J. Wang, W. Zhang, Quantitative diagnosis of a spall-like fault of a rolling element bearing by empirical mode decomposition and the approximate entropy method, Mech. Syst. Signal Process. 40 (1) (2013) 154–177.
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