基于平均停机时间率的劣化系统状态维修决策优化模型  

Optimal Condition-based Maintenance Decision-making Model for Deteriorating System Based on Average Downtime Rate

作　　者：王雷 王少华 张耀辉 WANG Lei;WANG Shao-hua;ZHANG Yao-hui(Equipment Support and Remanufacturing Department,Army Academy of Armored Forces,Beijing 100072,China)

机构地区：[1]陆军装甲兵学院装备保障与再制造系,北京100072

出　　处：《装甲兵工程学院学报》2018年第3期1-6,共6页Journal of Academy of Armored Force Engineering

基　　金：军队科研计划项目

摘　　要：采用Gamma过程描述劣化系统状态变化,建立了系统状态随机劣化模型。为降低劣化系统的平均停机时间率,在考虑检测时间和维修时间影响的条件下,利用更新过程理论,以系统长期运行平均停机时间率最小为优化目标,建立了以系统检测间隔期与预防性维修阈值为决策变量的状态维修决策优化模型。采用蒙特卡罗方法对模型进行优化求解,得到了系统最优检测间隔期与预防性维修阈值,并通过案例进行了分析,结果表明:采用优化得到的检测间隔期和预防性维修阈值进行状态维修决策,能有效降低劣化系统的平均停机时间率。The Gamma process is used to describe the condition change of the deteriorating system,and a stochastic deteriorating model for the system condition is established. To reduce the average downtime rate of the deteriorating system,in consideration of influence of inspection time and maintenance time and aiming at the minimization of the long run average downtime rate of the system,an optimal conditionbased maintenance decision-making model is established with the test interval and the preventive maintenance threshold value as decision-making variables based on the renewal process theory. The Monte Carlo method is used to optimize the model,and the optimal test interval and the preventive maintenance threshold are obtained. The case study result shows that the average downtime rate of the deterioration system can be effectively reduced by optimizing the test interval and the preventive maintenance threshold for the condition based maintenance decision-making.

关 键 词：状态维修 平均停机时间率 检测间隔期 预防性维修阈值 Gamma过程 蒙特卡罗仿真 

分 类 号：E92[军事—军事装备学]