In the light of the deficiency of the traditional hidden Markov model (HMM), a new method to evaluate the performance degradation of mechanical equipment is proposed. It is based on the hierarchical Dirichlet process (HDP) and continuous hidden Markov model (CHMM). First, the self-adaptive structure of model changes dynamically with relative data for the optimal degradation state parameters during the operation. Then, the equipment degradation state transition path is obtained with the analysis and modeling based on CHMM to identify and evaluate the degradation. Finally, the life characteristic values of rolling bearings are used as the data to verify the proposed method. The results are compared with those obtained by K-S algorithm. It shows that the proposed method of performance degradation assessment based on HDP-CHMM can be used to simulate equipment actual degradation process. It takes theoretical guidance for the maintenance of the equipment based on the state.