Neuro-fuzzy Based Condition Prediction of Bearing Health

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.