摘要
针对退化分布函数难以估计的复杂系统,研究了剩余寿命预测及预防性维护维修最优决策问题,提出一种基于复杂系统剩余寿命有效预测的预防性维护维修策略。在系统退化状态分布函数未知的条件下,由已知的设备寿命分布函数预测其平均剩余寿命,以平均剩余寿命为阈值制定预防性维护维修策略。根据更新过程理论,建立了以系统的预测间隔、预防性维护阈值为优化变量和最小化平均维护维修费用为目标函数的优化模型。采用微粒群算法进行优化求解,得到系统最佳的预测周期和维护维修阈值,并使系统长期运行的平均费用率最低。分别以在翼寿命符合威布尔分布的民航发动机和寿命分布符合正态分布的航海设备电控罗经中的某型变压器为例,验证了所提维护维修策略的可行性。
Aiming at the inestimable complicate system of degradation distribution function,the optimal decision for remaining useful life prediction and preventive maintenance was proposed,and a preventive maintenance strategy was presented based on effective prediction of remaining life for complex system.Under the conditions of unknown degradation distribution function,the average remaining useful life of the known life distribution function was forecasted as the threshold to draft preventive maintenance strategies.According to the theory of renewal process,an optimization model with the system prediction interval and the threshold of preventive maintenance as the optimization variables and the minimum average maintenance cost as the target function was established.By using Particle Swarm Optimization （PSO）,the optimal preventive cycle and maintenance threshold of system were obtained,and the long-run average cost rate was the lowest.The civil aeroengine operation of Weibull distribution and the transformer of electromagnet control gyrocompass in the navigation equipment of Normal distribution were taken as examples to verify the feasibility of proposed strategy.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2014年第5期1133-1140,共8页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(41272374)~~
关键词
剩余寿命
长期平均费用率
预防性维护维修
优化
remaining useful life
long-run average cost rate
preventive maintenance
optimization
