基于粒子群算法的装备预防性维修策略研究

Research on Equipment Preventive Maintenance Strategy Based on Particle Swarm Optimization Algorithm

为解决实战化条件下装备损耗严重和装备完好率之间的矛盾,立足实际提出加大预防性维修力度。根据装备可靠性理论和寿命分布理论,对装备故障率和役龄进行分析,并引入役龄回退因子进行修正。以装备服役期内预防性维修成本最低为目标函数,以可靠性为约束条件,建立预防性维修策略优化模型。采用粒子群算法对模型求解,并进行算例分析,得到装备在服役期内的最优预防性维修次数和时间间隔,证实了预防性维修模型的可行性和实用性。

In order to resolve the contradiction between serious equipment wear and equipment serviceability rate conditions under actual combat conditions,based on the actual situation,we propose to step up in preventive maintenance efforts.First,according to the equipment reliability theory and life distribution theory,the equipment failure rate and service life are analyzed,and a service life regression factor is introduced for correction.Secondly,an optimal model of preventive maintenance strategy is established with the minimum preventive maintenance cost during the equipment service period as the objective function and reliability as the constraint condition.Finally,the particle swarm algorithm is used to solve the model,and an example analysis is performed to obtain the optimal preventive maintenance times and time intervals of the equipment during the service period,which verifies the feasibility and practicability of the preventive maintenance model.