多故障流系统维修决策的半马氏模型

许多现有的系统维修模型仅仅考虑了一种类型的故障,并把系统的劣化状态作为决策的状态变量。但是,对于大型复杂系统这样的维修策略要应用可能是很困难的。在本文中提出了用于确定最优维修策略的半马尔可夫决策模型。这种模型考虑了大修与小修,系统假定在每次大修后都能“修复如新”。系统的故障流做为Weibull过程考虑。但是,故障则被分为多种不同的类型并且考虑了它们之间的相关性。维修决策的状态变量是当前故障类型及累计故障次数。模型的目标函数是找出使单位时间的运行维修费用最小化。作者还给出了求解模型的混合策略迭代仿真算法。并且本文还给出了一个说明性的算例。     

一种有价值的预防维修策略

当前,在系统的维修性方面,有许多概念是模糊的;许多行为是盲目的,至少是经验主义的。本文针对这些情况,提出了完整的科学维修的概念。以一个有使用价值的预防性维修策略为例,通过讨论,使这种科学维修的概念具体化,并且给出了系统的首翻期、维修周期以及更换期的严格定义和确定方法。     

基于粒子群算法的装备预防性维修策略研究

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.     

舰艇CGF搜潜过程马氏决策规划模型

舰艇搜索潜艇的过程可以近似地看作一种马尔可夫过程.研究了潜艇训练仿真系统中舰艇CGF(计算机生成兵力)搜索潜艇过程中的状态转移过程和随机搜索发现目标的概率模型,将舰艇CGF搜索潜艇的过程分为若干独立的阶段,建立了搜潜过程马氏决策规划模型,提出了在各种不同初始搜索状态下的舰艇搜索策略.仿真结果给出了舰艇CGF的最优搜索策略集合和发现概率,验证了马氏决策规划模型的有效性.     

MRO系统动态维修策略的建模与优化

在MRO系统中,随着对精益维修要求的日益提高,提出一种计算设备维护维修的最小平均费用率的模型。此模型是利用接收到的监控信息确定设备退化模型,设定退化模型动态预防性维修阈值,根据维修成本最小的原则动态选择最佳的预防性维护阈值和最佳的预防性维护时间。并计算各种不同参数下符合伽玛分布的退化模型的最小平均费用率,结论证明该模型的正确性和有效性。     

基于Wiener过程的动态性能检测视情维修策略

为了降低装备的维修成本,针对现有单部件系统视情维修策略研究中存在的性能检测时间缺乏灵活性,未充分利用部件退化状态信息的问题,采用wiener过程建立了单部件系统性能退化模型,给出了根据部件退化状态安排性能检测时间的方法;推导了预防性维修阈值的计算表达式,在此基础上提出了动态性能检测视情维修策略;案例对比分析表明,该维修...     

考虑任务的多设备串联系统预防性维修决策优化

针对多设备串联系统因分别对单一设备进行预防性维修而造成停机次数较多的情况,提出了考虑任务的多设备串联系统预防性维修决策优化方法,以期将使预防性维修的优化结果更贴近实际。首先,对考虑任务的多设备串联系统预防性维修进行了问题描述,然后,进行了建模假设,并以降低系统整机维修费用为目标,以成组维修和机会维修为维修策略调整的基本依据,以预防性维修费用和修复性维修费用的变化为变量,建立了考虑任务的多设备串联系统预防性维修决策优化模型。最后,以某型多设备系统为例,进行了算例验证。     

基于二维量度的复杂设备预防性维修决策优化

针对使用与维修具有两个测量维度的复杂设备,开展了其预防性维修决策的优化研究。基于二维量度的故障模式,给出了二维故障率的定量描述方法;分析了其预防性更换过程的基本过程,探讨了二维量度下更换周期对维修效果的影响,并从经济性角度建立了二维工龄更换费用模型;最后,采用算例的形式,对某设备维修决策同时考虑日历使用时间和行驶里程的情况,进行了二维更换间隔期的优化求解,从而验证了所建立方法与模型的实用性。     

美军军事决策过程

军事决策过程是军事行动过程中做出决策所应遵循的客观规律的理论总结,不仅是对指挥员主体能力的客观检验,也是对参谋等辅助决策人员军事素养的全面考核。美军经过一系列实战检验和训练实践,不断规范军事决策过程,形成了完善的决策程序,使之更加满足军事决策实战要求。文章阐述美军指挥员和参谋人员在军事决策中的职能以及军事决策的程序。针对作战时间紧迫的现实情况,对美军精简版军事决策过程和加速版军事决策过程的技术途径分别进行了解析。     

基于维纳过程金属化膜电容器的可靠性评估

金属化膜电容器作为惯性约束聚变(ICF)激光装置的重要元器件,其可靠性直接影响着系统的性能。为此,很多研究者对电容器的可靠性进行了评估,然而这些评估方法得到的只是电容器的总体特性,无法给出单个电容器的可靠性水平。鉴于此,提出了融合单个电容器性能退化数据与先验性能退化数据信息的可靠性分析方法,首先采用W inner过程对其性能退化过程进行建模;其次基于B ayes方法对单个电容器的可靠性进行实时评估;最后通过一个实例表明了其研究意义和实用价值。     

Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

随舰备件需求分析中维修策略问题

分析了面向任务保障性工程理论指导下的舰船随舰备件配置问题,就最大、最小两种维修策略下随舰备件配置问题进行了研究,给出了面向任务的随舰备件需求分析仿真模型框架,结合算倒,研究了最大维修策略与最小维修策略的适用时机:在任务确定且任务结构函数明确条件下,应采用最小维修策略;否则采用最大维修策略.     

Bayesian enhanced decision making for deteriorating repairable systems with preventive maintenance

Since a system and its components usually deteriorate with age, preventive maintenance (PM) is often performed to restore or keep the function of a system in a good state. Furthermore, PM is capable of improving the health condition of the system and thus prolongs its effective age. There has been a vast amount of research to find optimal PM policies for deteriorating repairable systems. However, such decisions involve numerous uncertainties and the analyses are typically difficult to perform because of the scarcity of data. It is therefore important to make use of all information in an efficient way. In this article, a Bayesian decision model is developed to determine the optimal number of PM actions for systems which are maintained according to a periodic PM policy. A non‐homogeneous Poisson process with a power law failure intensity is used to describe the deteriorating behavior of the repairable system. It is assumed that the status of the system after a PM is somewhere between as good as new for a perfect repair and as good as old for a minimal repair, and for failures between two preventive maintenances, the system undergoes minimal repairs. Finally, a numerical example is given and the results of the proposed approach are discussed after performing sensitivity analysis. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

策略不确定条件下基于高阶超博弈的军事对抗决策方法

军事对抗决策中面临的一个主要问题是难以确定敌方的策略集。基于超博弈分析策略不确定条件下的军事对抗决策问题。在分析超博弈中信念迭代原理的基础上,提出了基于高阶超博弈的对抗决策方法。将高阶信念中的结果反思到低阶信念,并最终反思到一阶信念中,将己方的决策建立在对敌方可能决策的分析的基础上。使得己方的决策具有针对性且更加合理。以二战中西线战役为例验证了方法的可行性和有效性。     

Nonperiodic preventive maintenance for repairable systems

As a complex system with multiple components usually deteriorates with age, preventive maintenance (PM) is often performed to keep the system functioning in a good state to prolong its effective age. In this study, a nonhomogeneous Poisson process with a power law failure intensity is used to describe the deterioration of a repairable system, and the optimal nonperiodic PM schedule can be determined to minimize the expected total cost per unit time. However, since the determination of such optimal PM policies may involve numerous uncertainties, which typically make the analyses difficult to perform because of the scarcity of data, a Bayesian decision model, which utilizes all available information effectively, is also proposed for determining the optimal PM strategies. A numerical example with a real failure data set is used to illustrate the effectiveness of the proposed approach. The results show that the optimal schedules derived by Bayesian approach are relatively more conservative than that for non‐Bayesian approach because of the uncertainty of the intensity function, and if the intensity function are updated using the collected data set, which indicates more severe deterioration than the prior belief, replacing the entire system instead of frequent PM activities before serious deterioration is suggested. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

机械设备视情维修决策系统的研究与开发

从技术的角度讨论了为机械设备开发维修决策支持系统的必要性、可行性及系统技术关键的解决策略,以及系统开发中对人力资源的需求,为开发这样的系统提供技术与管理上的支持.     

多核贝叶斯优化的模型决策树算法

构造模型决策树时超参数较多,参数组合复杂,利用网格搜索等调参方法将会消耗大量的时间,影响模型性能的提升。提出了一种多核贝叶斯优化的模型决策树算法,该算法为应对不同分类数据特性,采用三种高斯过程建模寻优,利用贝叶斯优化技术,选出最优的参数组合。实验结果表明,所提算法在参数寻优上要优于传统的模型决策树寻优方法,并且能够在迭代次数不多的情况下找到全局最优参数值,在一定程度上提升了算法的分类性能,节省了大量的调参时间。     

Optimal joint preventive maintenance and production policies

We study joint preventive maintenance (PM) and production policies for an unreliable production‐inventory system in which maintenance/repair times are non‐negligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to produce. We consider a discrete‐time system, formulating the problem as a Markov decision process (MDP) model. The focus of the work is on the structural properties of optimal joint policies, given the system state comprised of the system's age and the inventory level. Although our analysis indicates that the structure of optimal joint policies is very complex in general, we are able to characterize several properties regarding PM and production, including optimal production/maintenance actions under backlogging and high inventory levels, and conditions under which the PM portion of the joint policy has a control‐limit structure. In further special cases, such as when PM set‐up costs are negligible compared to PM times, we are able to establish some additional structural properties. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

装备预防性维修的维修级别逻辑决策分析方法

针对预防性维修的维修级别没有规范、统一的分析与确定方法的问题,研究了预防性维修的维修级别逻辑决策分析方法。明确了预防性维修的维修级别决策分析的对象是预防性维修工作类型,预防性维修主要有定时维修和状态维修,定时维修分为定时拆修和定时报废2种维修工作类型,状态维修分为状态信息检测、状态识别、状态预测、维修决策、故障诊断和维修实施等维修工作类型。根据维修间隔期、维修能力评估、其它非经济性因素以及经济性分析,分别建立了定时维修和状态维修的维修级别逻辑决策模型。     

基于Matlab优化工具箱和VB语言的消磁电流决策

针对舰船消磁电流决策问题,利用Matlab优化工具箱对舰船模型进行了消磁实验,取得了良好的消磁效果.还应用VisualBasic语言与Matlab混合编程,开发了实用的消磁电流决策软件,能够提高消磁电流的决策效率.