退化系统状态维修决策与维修活动建模

研究退化系统的状态维修决策问题，考虑经济性、可用性后，给出两个通用维修决策优化模型，用gamma过程对系统退化进行建模，用监测数据估计退化模型参数。在退化过程基础上，基于历史维修信息和状态数据对决策模型中的变量进行确定；对维修活动中主要的影响--维修效果和维修时间进行分析，认为维修效果和维修时间是系统状态和维修次数的随机变量，分别给出了不考虑人为因素和考虑人为因素的维修效果几何分布模型，用插值方法建立维修时间分布函数。最后以某控制系统为例，对比理想状态和考虑维修效果与维修时间下的仿真结果，验证了模型的有效性和实用性。

Condition based maintenance decision of deteriorating systems and modeling of maintenance actions

The condition based maintenance decision modeling of deteriorating systems is focused on. Considering the economic factors and system availability, two general maintenance optimization models are given. The gamma distribution is used to model the system degradation, and monitoring data are used to estimate the parameters. Then based on the deteriorating model, historical maintenance information and monitoring data are used to make certain variables in decision models. For the maintenance effects and maintenance time of the main impacts in maintenance actions, geometric distribution models are given to model maintenance effects with and without human factors respectively, which is considered as the random variable of system condition and maintenance numbers, and an interpolation method is used to construct the distribution function of maintenance time. Finally, the decision model is applied to a control system, and the comparison results of the decision model between ideal and random variable situation demonstrate the efficiency and practicability of the proposed models.