部分可观测信息条件下系统最佳检修策略分析

针对部分可观测信息条件下的退化系统，提出利用部分可观测马尔可夫决策过程模型解决系统视情维修问题。采用隐马尔可夫模型对系统进行状态评估，得到系统的转移概率和观测概率矩阵；利用比例故障率模型对系统进行可靠性分析，得到系统的故障率和可靠度函数，不仅考虑系统的工作时间，也考虑系统的退化状态。最后，以系统长期运行的最小平均费用率为目标，得到最佳的检测周期和最优的更换策略。实例研究表明，该方法可为保障人员提供科学的维修决策依据。

Analysis of optimal inspection and maintenance policy with partially observed information

The partially observable Markov decision processes model is proposed to solve the problem of condition based maintenance in the instance of the degraded system with partially observable information.Firstly,the hidden Markov model is used for state evaluation to get the transition probability and observation probability of the system.Secondly,the proportion hazards model is used for reliability analysis to get the failure rate and reliability function of the system,which considers not only the working time,but also the degradation state of system.Finally,aiming at the rate of the minimum average cost in a long term operation,the best inspection interval and optimal replacement strategy are gotten.A case study indicates that the method can provide a scientific reference of maintenance decision for maintenance personnel.