Abstract: The bearing vibration signal contains a large amount of information involved in degradation of spindle system. The adding-weight one-rank local-region method is used to predict the vibration time series for bearing, and the forecasting error can be obtained by comparing and analyzing the prediction values with the actual values so as to verify the feasibility of the model. The prediction results of the future state for the bearing are processed by grey bootstrap method, and the vibration thresholds are given by the requirements of the spindle system on the bearing vibration performance. The performance reliability prediction of the bearing is realized by the Poisson process. Investigation shows that the prediction results of forecasting model are true and reliable for vibration performance with the maximum relative error only 13.92%; reliability curves can describe the performance degradation process of bearings accurately. The proposed model can be used for health monitoring and forecasting of bearings performance, and can detect hidden dangers in time.

Key words: bearing, vibration, chaotic theory, grey bootstrap method, reliability