复杂装备网络化智能维护架构研究

针对复杂装备所面临的智能维护问题,进行了复杂装备的网络化智能维护架构理论研究,以满足装备保障的需要。首先,建立了复杂装备网络化智能维护的架构模型;其次,探讨了各部分的功能和系统实现的关键技术,并对其进行了性能分析;最后,将其应用到某型自行火炮的网络化智能维护中。结果表明,建立的复杂装备网络化智能维护架构具有可行性、可靠性和可扩展性,是进行复杂装备智能维护的一种全新的途径。     

创新中国特色的装备再制造工程构建我军装备维修保障新型学科

介绍了中国特色的装备再制造工程的内涵与特征,论述了装备再制造在装备维修保障中的地位和作用,分析了构建装备维修保障新型学科——“装备再制造与战场抢修”的重要性,阐述了装备再制造对于提高装备维修保障能力,提升装备综合保障效能,提高装备质量、效益与核心战斗力具有重要意义。     

装备精确修理浅析

如何用有限的装备修理力量,在战役全过程中尽可能多地修复战损装备,提高装备参战率,是战役装备修理的任务.提出精确修理以装备动态需求为依据,通过优化装备修理各要素,为战损装备提供"精确"的服务,来实现装备修理的快速高效,并通过建立修理人员效能评估模型,说明精确修理的高效性.     

BP组合预测方法在维修保障费用预测中的应用

通过对时间序列预测方法和回归分析原理的分析,建立了适用于武器装备维修保障费用的BP网络组合预测的时间序列多输出模型,并结合某型装备多年的维修保障费用,进行了预测数据仿真,得出的结果与实际的数据相比误差较小,具有较大的理论价值和实际的军事价值,有利于提高维修保障费用的效益,有利于实现装备的优良效费比。     

数据基故障诊断算法更新问题研究

机内测试被广泛应用于故障诊断、装备健康管理与预测等领域。针对机内测试设备在设计和升级时遇到的分类器更新、样本数量不平衡、硬件条件限制问题,提出初步解决方案。利用基于密度的聚类和人工免疫方法处理原始数据;提出基于代表样本点的混合学习方法;利用支持向量机和仿真案例验证所提方法。结果表明所提方法能够解决上述问题,有助于基于数据的机内测试设备设计与升级。     

Block replacement policies for a two‐component system with failure dependence

Block replacement and modified block replacement policies for two‐component systems with failure dependence and economic dependence are considered in this paper. Opportunistic maintenance policies are also considered. Where tractable, long‐run costs per unit time are calculated using renewal theory based arguments; otherwise simulation studies are carried out. The management implications for the adoption of the various policies are discussed. The usefulness of the results in the paper is illustrated through application to a particular two‐component system. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

基于虚拟样机的导弹维修训练仿真系统

以虚拟样机技术为基础 ,提出了装备虚拟维修训练系统建设总体方案 ,主要用于解决目前武器装备维修训练采用实物、实兵、实地训练 ,日常训练成本高、危险性大、训练效率与训练效果有待提高的问题。采用虚拟样机技术开发的装备维修仿真训练系统是解决目前武器装备维修训练突出问题的有效途径。该系统的实现 ,对于解决目前存在的复杂装备维修训练问题有重要意义     

基于Pareto排序法的战时装备维修任务多目标调度方法

针对战时武器装备维修保障问题,建立了包括最大完工时间、延迟时间和维修单元负荷在内的多目标优化调度模型。为提高解的多样性和收敛性,构建了一种基于Pareto排序法和小生境技术相结合的遗传算法用于模型求解,引入Pareto排序和拥挤距离进行适应度计算,通过混沌系统随机生成权重系数,并使用小生境技术改进选择方式。通过实例验证表明,该方法能够有效地解决装备维修多目标调度问题。     

Optimizing usage and maintenance decisions for k‐out‐of‐n systems of moving assets

We consider an integrated usage and maintenance optimization problem for a k‐out‐of‐n system pertaining to a moving asset. The k‐out‐of‐n systems are commonly utilized in practice to increase availability, where n denotes the total number of parallel and identical units and k the number of units required to be active for a functional system. Moving assets such as aircraft, ships, and submarines are subject to different operating modes. Operating modes can dictate not only the number of system units that are needed to be active, but also where the moving asset physically is, and under which environmental conditions it operates. We use the intrinsic age concept to model the degradation process. The intrinsic age is analogous to an intrinsic clock which ticks on a different pace in different operating modes. In our problem setting, the number of active units, degradation rates of active and standby units, maintenance costs, and type of economic dependencies are functions of operating modes. In each operating mode, the decision maker should decide on the set of units to activate (usage decision) and the set of units to maintain (maintenance decision). Since the degradation rate differs for active and standby units, the units to be maintained depend on the units that have been activated, and vice versa. In order to minimize maintenance costs, usage and maintenance decisions should be jointly optimized. We formulate this problem as a Markov decision process and provide some structural properties of the optimal policy. Moreover, we assess the performance of usage policies that are commonly implemented for maritime systems. We show that the cost increase resulting from these policies is up to 27% for realistic settings. Our numerical experiments demonstrate the cases in which joint usage and maintenance optimization is more valuable. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 418–434, 2017     

基于灰色局势决策的通用维修资源整合方法

维修资源是装备保障系统的重要组成部分,针对部队装备维修资源品种越来越多、保障负担越来越重的问题,分析了通用维修资源的优点,提出了一种基于灰色局势决策理论的通用维修资源整合方法,并给出了具体实施步骤,主要包括构建决策目标体系、制定决策流程、计算综合测度和选择决策等,最后还进行了详细的案例研究.为维修资源的有效整合提供了决策依据和科学方法,对于减少维修资源种类、提高装备保障效率具有一定的指导作用和应用价值.