多状态串联维修系统的检测及维修优化

Inspection and Maintenance Optimization of Multi-State Series Repairable System

对系统进行维修优化时,不仅要考虑系统自身可靠性特性,还应充分利用检测数据并优化检测策略。以串联可修多状态系统为研究对象,以降低系统运行成本率为目标,在考虑检测误差和非完美维修的情况下,实现检测和维修优化。使用非齐次离散马尔可夫过程建立系统退化模型和可靠性分析模型,采用贝叶斯更新方法利用检测数据更新可靠性分析结果,设置可靠性相关阈值触发维修,对系统长期运行过程进行蒙特卡洛仿真,并在仿真环境下基于遗传算法实现策略寻优。通过算例验证了上述方法的有效性,为维修系统优化提供了科学依据。

For system maintenance,it is not only to consider the reliability characteristics of the system itself,it should also make full use of the inspection data and optimize the detection strategy.A series repairable multi-state system is studied and in order to reduce the operating cost of the system as the goal,inspection and repair optimization is achieved under the condition of considering the inspection error and imperfect repair.Non-homogeneous discrete Markov process is used to establish the system degradation model and reliability analysis model,and the Bayesian updating method is used to update the reliability analysis results with the given inspection data.Reliability related thresholds are set up to trigger the repairs,and the system long-term operating process is simulated by a Monte Carlo simulation.Strategy optimization is achieved by a genetic algorithm in the simulation environment.The effectiveness of the proposed method is verified by a numerical example.