Characterization of Fault Size in Bearings

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Published Sep 29, 2014
Matan Mendelovich Yitschak Sanders Gideon Kogan Mor Battat Renata Klein Jacob Bortman

Abstract

Bearings are important components in rotating machines. An initial small damage in the bearing may cause a fast degradation, which may lead to the machine breakdown. The health condition of bearings can be monitored using proven vibro-acoustic methods effective for detecting bearing faults. However, the existing bearing health indicators do not provide a reliable estimation of the fault characteristics, such as fault size and fault location. As a result, the ability to assess the severity of the bearing damage and to make maintenance decisions is limited.The presented study is a part of an ongoing research on bearing prognostics, aimed to improve the understanding of the effects of fault size on the bearing dynamics. The research methodology combines dynamic modeling of the faulty bearing with experimental validation and confirmation of model simulations.

In the presented study, small faults (starting from 0.3 mm), simulating incipient damage are generated at increasing sizes by an electrical discharge machine. The recorded vibration data is then analyzed and compared to the vibration signatures predicted by the model. The experimental and the simulation results add new insights on the manifestation of the size of the fault and possible indicators of the damage severity.

How to Cite

Mendelovich, M. ., Sanders, Y., Kogan, G. ., Battat, M. ., Klein, R. ., & Bortman, J. . (2014). Characterization of Fault Size in Bearings. Annual Conference of the PHM Society, 6(1). https://doi.org/10.36001/phmconf.2014.v6i1.2387
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Keywords

PHM

References
Sawalhi, N., & Randall, R. B. (2008). Semi-automated bearing diagnostics – three case studies. School of Mechanical and Manufacturing Engineering. The University of New South Wales, Sydney, Australia.
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N. Sawalhi, R.B. Randall. (2011). Vibration response of spalled rolling element bearings: Observations, simulations and signal processing techniques to track the spall size. Mechanical Systems and Signal Processing 25 (2011) 846–870
Kogan, G., Bortman, J., Kushnirsky, A., & Klein, R. (2012). Ball bearing modeling for faults simulation, Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, no. 1, pp. 1–8.
Kogan G., Shaharabany S., Itzhak I., Bortman J. & Klein R., (2013). Towards Model Based Prognostics - Characterization of Fault Size in Bearings, Annual Conference of the PHM Society 2013.
Section
Technical Research Papers

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