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Neuro-fuzzy Based Condition Prediction of Bearing Health

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China, fagang{at}sjtu.edu.cn

Jin Chen

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China

Lei Guo

State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China

Xinglin Li

State Test Laboratory of Hangzhou, Bearing Testing & Research Center, Hangzhou, 310088, China

A reliable prognostic model is very useful for industries to forecast equipment behaviors. The aim of this research is to verify the effectiveness of the neuro-fuzzy model in predicting the health condition of bearings. Simulation and an experiment have been carried out to verify the model, with results showing that the neuro-fuzzy model is a reliable and robust forecasting tool, and more accurate than a radial basis function network. In the experiment, vibration data collected from the equipment is used to predict the future condition.

Key Words: Prediction • neuro-fuzzy • bearing vibration • RBF network.

This version was published on July 1, 2009

Journal of Vibration and Control, Vol. 15, No. 7, 1079-1091 (2009)
DOI: 10.1177/1077546309102665


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