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中文摘要：
视情维修可以根据设备工作状况安排预防性维修措施,是解决退化失效问题、保证设备可用度的有效途径。以无人机核心部件为研究对象,将部件在运行中发生的缓慢劣化过程,划分为若干个性能劣化状态。利用连续时间马尔可夫链理论建立状态维修及更换策略模型。以设备的稳态最大可用度为决策指标,同时考虑相邻两个阶段的平均劣化时间、平均检测时间、平均预防性维修时间以及更换部件时间等因素的影响。根据马氏过程平稳状态下的统计平衡原理,采用递归求解的算法对模型进行求解,最终确定系统最优检测频率、视情维修阈值和更换策略。实验结果表明,该模型能有效描述设备的劣化过程,实现设备维修优化。
英文摘要：
Condition-based maintenance can arrange preventive maintenance according to the operating condition of the equipment,which is an effective way to solve the degradation failure and ensure the availability of equipments. In this paper,we focuse on the core components of the UAVs and develop the condition-based maintenance model as well as replacement policy with the method of continuous-time Markov chain by dividing the deterioration into different states happened in the operational process. In the model,the maximal steady state availability of the system is used as the indicator to arrange maintenance,while the impact of the such factors as average time of the deterioration between two adjacent stages,the average detection time,the average time of preventive maintenance and the time for part replacing and etc,is also taken into account.Ultimately,the optimal frequency of testing system and the threshold of condition-based maintenance as well as the replacement policy are determined by using a recursive algorithm to solve the model according to the principle of statistical equilibrium in the steady state of Markov process. The result shows that the presented the model can describe the degradation process effectively,and can be used to optimize the maintenance policies.
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