某型武装直升机武器系统故障诊断研究

战时快速准确地查找故障部件和制定排故方案是实施战场抢修的前提和基础。目前武装直升机武器系统结构组成日趋复杂,功能模块高度集成,仅凭人工经验进行维护难度较大。为了提高故障诊断效率,采用故障树分析与专家经验相结合的方法,建立了某型武装直升机武器系统故障模型,设计了一种快速故障诊断与辅助决策系统,有效减少了维修保障人员故障排除时间,提升了故障处置效率与准确度,具有重要的实际应用价值。     

关于图的n-Irredundance数和n-Domination数

设G是简单连通图,r_n~c(G)和ir_n(G)分别表示图G的连通n-Domination数和n-Irredundance数、本文证明了如下结论:r_n~c(G)≤(3n+1)ir_n(G)-2n。     

坦克稳定器和电气故障诊断系统

现役59式坦克稳定器和电气系统,由于研制时测试性设计不周,在使用中一旦发生故障,如何迅速排除,在部队一直是个老大难问题.使用本故障诊断系统,能够指导维修人员快速找到发生故障的部件或外部电路;可以在显示器上用颜色作相应变化的电路图,一步步演示出故障压缩过程,直至最后找出故障部位.本文将介绍该系统的功能、技术方案、技术关键及使用特点.     

舰艇智能化管理系统探讨

针对舰艇装备自动化程度的日益提高 ,结合智能化管理系统 ,在具体分析舰艇各个系统的基础上 ,采用结构优化模式 ,提出了总体结构方案 ,并对关键技术的应用加以讨论     

弹炮结合武器系统作战效能评估

弹炮结合系统是一种有效的防空武器系统,但以往对该武器系统的作战效能评估存在两方面不足:一是较少考虑攻防双方的对抗以及环境对作战效能的影响,使得出的指标可信度降低;二是不同国度、类别、型号的武器系统没有构建统一的价值可比空间,使获得的指标缺乏横向可比性.为此利用灰色关联综合优化法有关原理,给出弹炮结合防空系统作战效能的评价指标体系,确立了相关的隶属函数,进而通过六种弹炮结合防空系统作战效能的优劣排序,验证了该方法有效可行,初步解决了上述问题.     

Noncooperative cost spanning tree games with budget restrictions

We extend the noncooperative game associated with the cost spanning tree problem introduced by Bergantiños and Lorenzo (Math Method Oper Res 59(2004), 393–403) to situations where agents have budget restrictions. We study the Nash equilibria, subgame perfect Nash equilibria, and strong Nash equilibria of this game. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2008     

谈事故树分析法在企业消防安全管理中的运用

介绍了事故树法的原理，运用该方法对镇江市某大型醋酸生产企业醋酸反应釜单元进行了火灾爆炸危险性分析，并结合分析结果给出了有针对性的消防安全对策，为企业消防安全管理工作提供了借鉴。     

雷达网信息传输能力评估算法动态仿真

基于对连通概率、时效性函数、误信率的具体界定,对雷达网的信息传输能力进行了系统的研究。提出了一种具有良好操作性的定量评估方法,并对传输时延动态估计算法进行了仿真。     

人员密集场所火灾亡人事故成因探讨

通过构建火灾亡人事件树、早期确认火灾失败故障树、火场逃生自救失败故障树和外部抢险救援失败故障树,获得了人员密集场所火灾亡人事故因果分析图。对1991年至2007年发生在我国人员密集场所的22起特别重大火灾亡人事故按照因果分析图进行统计分析,得出了人员密集场所火灾亡人事故成因。     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.