Abstract: As a vital part of a gasifier,the residual thickness and residual life of refractory bricks determine the performance and operational safety of the gasifier. Therefore,it is necessary to formulate a reasonable maintenance plan for the refractory bricks. Condition-based Maintenance (CBM) can reduce maintenance risks and costs,and ensure the reliability of the gasifier. For this purpose,the focus was on the accurate diagnosis of health state and the accurate prediction of the residual life of refractory bricks in this study. A health state diagnosis model and a residual life prediction model for gasifier refractory bricks were constructed,and a related study was conducted on the refractory bricks lining the combustion chamber of a company's gasifier under actual working conditions. The research process is as follows:① The initial parameters of the model were determined by the K-means algorithm. The model corresponding to the each state of the refractory bricks was trained by the improved Baum-Welch algorithm. The loglikelihood probabilities of the test sequence and each state model were calculated and compared in size by the improved Viterbi algorithm,where the state corresponding to the state model that got the largest log-likelihood probability was the state of the test sequence. ② The whole life cycle model was trained with the refractory brick whole life data and the residual life of each state was predicted based on the revalued model parameters. ③ The current residual life of the refractory brick was predicted based on the health state diagnosis results. The results obtained based on the HSMM were also compared and analyzed with those obtained based on the HMM as well as the actual values. The results show that the HSMM-based health state diagnosis of refractory bricks achieves a correct rate of 95%,which is greater than the HMM-based rate of 92.5%. The residual life prediction for each state of refractory bricks obtained from the HSMM all fall within the actual residual life interval,with an average correct rate of 81. 36%,which is higher than the HMM-based average correct rate of 71.22%. It indicates that the constructed refractory brick health state diagnosis and residual life prediction models are in line with the actual degradation pattern of gasifier refractory bricks and have achieved good results.