Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions
Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions作者机构:College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China Jiangsu Key Laboratory of Internet of Things and Control TechnologiesNanjing University of Aeronautics and AstronauticsNanjing 211106China School of Earth Sciences and EngineeringHohai UniversityNanjing 211100China
出 版 物:《Journal of Systems Engineering and Electronics》 (系统工程与电子技术(英文版))
年 卷 期:2020年第31卷第4期
页 面:841-851页
核心收录:
学科分类:0808[工学-电气工程] 07[理学] 0809[工学-电子科学与技术(可授工学、理学学位)] 0802[工学-机械工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:supported by the National Natural Science Foundation of China(61873122) the Priority Academic Program Development of Jiangsu Higher Education Institutions。
主 题:condition-based maintenance(CBM) imperfect maintenance maintenance cost availability constraint optimization
摘 要:Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.