According to the acquisition of inspection and maintenance information of civil aeroengine hotsection subassembly system and typical degradation state judgment by experts

the models of sojourn time estimation of each typical macro degradation state based on expert estimation opinion

inspection information and their fusion data were set up under the assumptions of the system state degradation process obeying a discrete semiMarkov chain. The methods of maximum likelihood estimation and MCMC(Monte Carlo Markov Chain) were applied to estimate the model parameters

the sojourn time and the state transition coefficients in each macro degradation state based on these three kinds of data. Meanwhile

the state transition probability models were built in a certain service cycle for optimal inspection and maintenance cost

and then the optimal inspection intervals in three typical macro degradation states

ie 1750

350

70cycles were obtained by simulation. The results showed the optimal inspection intervals were relatively close to the reality situations in the civil aviation operation and production

providing the technical supports in the aspect of customeroriented inspection and maintenance decisionmaking and improving economic benefits for civil aviation transport enterprises.