基于最大后验概率候选集更换法的多故障诊断策略研究

给出了一种基于最大后验概率候选集更换法的多故障诊断策略，并深入阐述了基于最大后验概率候选集更换法的形式化描述，分析了对单故障诊断和多故障诊断的计算模型，提出了基本的故障诊断算法——改进二进制粒子群算法，并对抽象实例进行验证，结果表明，采用改进BPSO算法能有效地求解基于最大后验概率候选集更换法的多故障诊断问题。     

支持向量机技术的雷达板级电路快速故障诊断

介绍了支持向量机的基本原理.针对目前雷达装备诊断过程中存在的可更换板级电路多、传统诊断方法不理想等问题,提出了一种基于支持向量机的雷达板级电路快速诊断方法.建立了故障诊断样本训练和测试平台,对某型雷达预调器板进行了故障诊断实验.结果表明,该方法诊断准确性高,比其他方法更为快速有效,较好地解决了雷达可更换板级电路的故障诊断问题.     

消息密钥的产生与密钥修改的微机实现

为了提高模拟保密机的抗破译能力,在基本密钥不经常更换的情况下,应配置足够数量的消息密钥以及密钥修改装置。在微机控制的模拟保密机里,怎样尽量利用软件产生消息密钥以及进行密钥修改,是提高保密机性能/价格比的重要实际问题。本文第一部分阐述了三种软件产生消息密钥的方法,第二部分介绍了一种密钥修改装置。     

考虑不完全维修的装备单元维修与更换策略优化

针对装备单元维修与更换策略优化问题,采用齐次马尔科夫模型描述了装备单元的退化规律,结合准更新过程建立了考虑不完全维修的装备单元维修与更换策略权衡优化模型,并利用模型对装备单元的维修费用与更换策略进行了优化,旨在实现装备单位时间的净效益最大化,最后通过算例验证了模型的有效性,研究成果可为制定装备单元的维修与更换策略提供理论参考。     

基于年龄更换策略的威布尔分布备件需求计算方法

备件需求量预测在装备保障工作中发挥着重要作用。预防性维修可以消除装备潜在的故障或避免装备发生故障后所导致的严重后果,从而使装备始终处于期望状态。预防性维修策略下备件需求量建模能够以可预见的可靠性数据为基础进行,其关键问题是最佳更换间隔时间的确定。针对威布尔分布装备备件,采用年龄更换策略,确定最佳更换间隔时间,并在此基础上导出威布尔型备件需求计算模型,为备件需求量的预测提供了一种简单有效的方法。     

基于IVI的机载导弹测试设备设计

设计了一种基于可互换虚拟仪器的机载导弹测试设备,分析了设备的软硬件结构,研究通过程序、配置文件管理硬件,使得更换硬件时测试程序改动程度最少,增强了测试设备的通用性.     

飞控动基座对准性能桌面测试系统设计

针对飞控动基座对准因为外部信息不断变化导致性能测试无法覆盖动态过程的问题,提出了一种基于MFC和Matlab语言开发的飞控动基座对准性能桌面测试系统。该系统具备设置测试环境、测试首次收敛时间、评估收敛品质、测试导航误差等功能。通过更换Matlab数字仿真动态库文件,可实现动基座对准桌面测试的通用化。     

基于Dempster-Shafer证据理论的特征融合在军用电子设备模块化故障诊断过程中的应用

军用电子设备的维修是以更换电子集成模块为主,根据这一特点,通过分析处理电子设备的故障特征信息,把一种基于D-S证据理论的算法应用于故障特征信息的融合,从而实现故障电子模块的定位.结合实例,论证了这一方法在军用电子设备模块化故障诊断中的可行性.     

大同大融合——山西省大同市致力军地融合发展呈现双赢局面

前不久的一天上午9时许,60台大吨位交通运输车浩浩荡荡行进在大同市"同左"公路上。眨眼间,车队披上了绿色伪装网,和所处地域融为一体;有的则装上了车体广告,汇入车水马龙的车流。就在人们惊叹之时,更换车头、更换     

集成电路在线测试系统的研究

集成电路的广泛应用 ,使得电路向集成化、小型化的方向发展。同时也给电路的测试、维护带来不便。一些只需更换损坏的集成电路这样简单的事情 ,由于没有一种简单快捷的测试手段而使电路设备不能正常工作。目前现有的集成电路测试设备价格高 ,操作复杂。针对这种现状 ,研究开发了一种快捷方便、具有一定智能化的集成电路测试系统     

有限马氏链最优停止的线性规划解

离散时间的有限状态马尔可夫链最优停止的值函数存在的一个充分条件是所对应的线性规划有解,且其最优解等于值函数,本文证明这个条件还是必要的。     

Target selection in Lanchester combat: Linear-law attrition process

We develop the solution to a simple problem of target selection in Lanchester combat against two enemy force types each of which undergoes a “linear-law” attrition process. In addition to the Pontryagin maximum principle, the theory of singular extremals is required to solve this problem. Our major contribution is to show how to synthesize the optimal target selection policies from the basic optimality conditions. This solution synthesis methodology is applicable to more general dynamic (tactical) allocation problems. For constant attrition-rate coefficients we show that whether or not changes can occur in target priorities depends solely on how survivors are valued and is independent of the type of attrition process.     

基于粗糙集和TOPSIS的弹药目标匹配研究

针对多种弹药打击同一目标的弹种选取顺序问题,即弹药目标匹配顺序问题,从弹药毁伤和目标抗毁伤机理人手,构建弹药目标匹配指标体系,利用粗糙集理论约简弹药目标匹配指标体系并确定指标的客观权重,运用加权TOPSIS确定弹药目标综合匹配顺序,为最优火力分配决策提供了理论依据。     

直升机攻潜时的接近航向

直升机攻潜策略是反潜战中值得研究的一个问题。研究攻潜策略实质是确定最优投雷点,即直升机的最优接近航向和投雷时刻。本文研究的结果是:如果目标作等速直线运动,则直升机的最优接近策略为平行接近法。     

On the isbell and marlow fire programming problem

A complete solution is derived to the Isbell and Marlow fire programming problem. The original work of Isbell and Marlow has been extended by determining the regions of the initial state space from which optimal paths lead to each of the terminal states of combat. The solution process has involved determining the domain of controllability for each of the terminal states of combat and the determination of dispersal surfaces. This solution process suggests a solution procedure applicable to a wider class of tactical allocation problems, terminal control attrition differential games. The structure of optimal target engagement policies in “fights to the finish” is discussed.     

The use of dynamic programming methodology for the solution of a class of nonlinear programming problems

This paper presents an application of a method for finding the global solution to a problem in integers with a separable objective function of a very general form. This report shows that there is a relationship between an integer problem with a separable nonlinear objective function and many constraints and a series of nonlinear problems with only a single constraint, each of which can be solved sequentially using dynamic programming. The first solution to any of the individual smaller problems that satisfies the original constraints in addition, will be the optimal solution to the multiply-constrained problem.     

Optimal power control in a wireless network using a model with stochastic link coefficients

This paper addresses optimal power allocation in a wireless communication network under uncertainty. The paper introduces a framework for optimal transmit power allocation in a wireless network where both the useful and interference coefficients are random. The new approach to power control is based on a stochastic programming formulation with probabilistic SIR constraints. This allows to state the power allocation problem as a convex optimization problem assuming normally or log‐normally distributed communication link coefficients. Numerical examples illustrate the performance of the optimal stochastic power allocation. A distributed algorithm for the decentralized solution of the stochastic power allocation problem is discussed. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Solving generalized transportation problems via pure transportation problems

This paper investigates certain issues of coefficient sensitivity in generalized network problems when such problems have small gains or losses. In these instances, it might be computationally advantageous to temporarily ignore these gains or losses and solve the resultant “pure” network problem. Subsequently, the optimal solution to the pure problem could be used to derive the optimal solution to the original generalized network problem. In this paper we focus on generalized transportation problems and consider the following question: Given an optimal solution to the pure transportation problem, under what conditions will the optimal solution to the original generalized transportation problem have the same basic variables? We study special cases of the generalized transportation problem in terms of convexity with respect to a basis. For the special case when all gains or losses are identical, we show that convexity holds. We use this result to determine conditions on the magnitude of the gains or losses such that the optimal solutions to both the generalized transportation problem and the associated pure transportation problem have the same basic variables. For more general cases, we establish sufficient conditions for convexity and feasibility. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 666–685, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10034     

On the treatment of force-level constraints in times-equential combat problems

The treatment of force-level constraints in time-sequential combat optimization problems is illustrated by further studying the fire-programming problem of Isbell and Marlow. By using the theory of state variable inequality constraints from modern optimal control theory, sharper results are obtained on necessary conditions of optimality for an optimal fire-distribution policy (in several cases justifying conjectures made in previous analysis). This leads to simplification of the determination of the domains of controllability for extremals leading to the various terminal states of combat. (Additionally, some new results for the determination of boundary conditions for the adjoint variables in optimal control problems with state variable inequality constraints have arisen from this work.) Some further extensions of previous analysis of the fire-programming problem are also given. These clarify some key points in the solution synthesis. Some important military principles for target selection and the valuation of combat resources are deduced from the solution. As a result of this work, more general time-sequential combat optimization problems can be handled, and a more systematic solution procedure is developed.     

基于粒子群优化算法的空中目标定位

受干扰条件下,雷达难以对空中目标准确定位。针对这一问题,提出了当多基雷达接收站在空间随机分布时,利用粒子群优化算法解决根据到达时间差对空中目标定位中遇到的非线性最优化问题。所建算法首先初始化一个随机粒子群,然后根据适应度值更新粒子速度和位置,通过迭代搜索最佳坐标。仿真结果表明,在参数设定合理的情况下,该算法性能稳定,能找到逼近全局最优点的解。