不完全维修条件下的视情维修优化模型

Optimal analysis of the condition-based maintenance model under the imperfect repair

针对实际工作中系统无法通过维修手段恢复如新的情况,利用离散状态的马尔可夫过程,将一类基本的不完全维修模型与视情维修理论相结合,建立了劣化系统在不完全维修条件下的视情维修模型。根据马氏过程平稳状态下的统计平衡原理,提出了求解系统稳态可用度的一类解析算法,并在此基础上,以系统稳态可用度最大为优化目标,确立了不完全维修条件下劣化系统的最佳检测间隔时间和视情维修阀值。最后,通过具体算例验证了了模型与算法的可行性。

To describe the fact that a system can not be as good as a new one through repairs in the real work, a new condition-based maintenance （CBM） model under the imperfect repairs is developed for the deteriorating system. By the discrete-state Markov process,it combines a basic imperfect repair model with the theory of CBM. Based on the statistical characteristic of embedded Markov chain, an algorithm is presented to get the analytical solution of steady-state availability. On the basis of the results, the joint optimization of inspection rate and the threshold value of CBM under the imperfect repairs are investigated for the maximization of system steady-state availability. At the end, the feasibility of the model and algorithm is verified through a numerical example.