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Aiming at the nonlinear and non-stationary time series generated by mechanical equipment, the AR algorithm is used to smooth the non-stationary data and determine the order of the model .Then, the SVR algorithm is used to fit the stationary data, and the PSO Algorithm to optimize SVR algorithm parameters. The model is used to predict the degradation trend of rolling bearings. Firstly, the time domain and frequency domain characteristics of the bearings are extracted, and then the data are predicted based on the data after PCA dimension reduction.. Finally, the results of this model are compared with those of AR and PSO_SVR alone. The experimental results show that the model is better.