A new concept on the degree of creditability of parameter value variations (DCPV factor) is proposed in this paper to solve problem that on-line monitoring and failure diagnosis of rolling element bearings are affected by monitoring parameter value variations caused by the intrusive vibration signals. Using the factor of the degree of creditability and the basic principle of the expert system, an on-line monitoring and diagnostic method of rolling element bearings with AI is developed. The technique enhances traditional vibration analysis and provides a means of automating the monitoring and diagnosis of vibrating device.
CITATION STYLE
Shao, Y., & Nezu, K. (1995). On-line monitoring and diagnostic method of rolling element bearing with AI. In Proceedings of the SICE Annual Conference (pp. 1543–1548). Society of Instrument and Control Engineers (SICE). https://doi.org/10.9746/sicetr1965.32.1287
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