主元分析法和模糊积分的航空发动机气路状态监测

航空发动机是一个大系统,由于结构复杂、工作条件恶劣等因素影响,对其进行有效地健康状态监测成为航空领域长期难以解决的关键技术之一。为有效监测航空发动机健康状态,以航空发动机气路系统为例,提出一种基于主元分析和模糊积分的航空发动机状态监测方法。首先,利用主元分析法提取发动机状态样本集的主元,对样本数据进行降维,实现样本的最优压缩。其次,利用BP神经网络和Elman神经网络对发动机状态信息的特征向量进行初步状态监测。最后,利用模糊积分对采用两种神经网络的初步监测结果进行决策层融合,从而有效地实现对航空发动机气路系统的状态监测。通过某型真实航空发动机验证表明,所提出基于主元分析和模糊积分的状态监测方法,能有效提高监测的准确度,满足航空发动机状态监测的实时性要求,具有良好的工程应用价值。     

政治警官个性心理特征与岗位匹配初探

提升工作效率和促进人生成功是个性心理特征与岗位匹配的逻辑起点,在部队政治工作中实现政治警官个性心理特征与岗位匹配,对于提高政治工作效益有着十分重要的现实意义.更新选用理念,创新测量技术,完善选用制度是实现政治警官个性心理特征与岗位匹配的有效路径.     

无线传感器网络动态汇聚节点调度算法研究

移动汇聚节点调度是传感器网络中一个新的研究热点.通过建立一个普适的多目标优化模型,提出了贴近实际的汇聚节点循环路径规划模型,采用以连续时间离散化为理论基础的时域-空域转化方法,将时域中的优化模型无损地转至空域中,从而大大减少了所涉及的变量数量,降低了求解的复杂度.通过实验可以看出,调度移动汇聚节点可以有效扩展网络的生命周期.     

New results on a stochastic duel game with each force consisting of heterogeneous units

Two forces engage in a duel, with each force initially consisting of several heterogeneous units. Each unit can be assigned to fire at any opposing unit, but the kill rate depends on the assignment. As the duel proceeds, each force—knowing which units are still alive in real time—decides dynamically how to assign its fire, in order to maximize the probability of wiping out the opposing force before getting wiped out. It has been shown in the literature that an optimal pure strategy exists for this two‐person zero‐sum game, but computing the optimal strategy remained cumbersome because of the game's huge payoff matrix. This article gives an iterative algorithm to compute the optimal strategy without having to enumerate the entire payoff matrix, and offers some insights into the special case, where one force has only one unit. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 56–65, 2014     

基于最少谓词思想的可达路径选择

对于结构测试中的不可达路径问题,仅仅使用传统的不可达路径排除方法存在很大的限制性,应用效果一般.积极选择可达路径的思想可有效减少不可达路径的产生.目前,基于最少谓词思想的路径生成方法得到广泛的认可.了解可达路径选择思想后,主要介绍一种基于数据流信息的,具体应用基本程序切片技术来生成可达路径的方法,该方法可生成几乎有最少谓词的路径,有较好效果.     

封套封存环境透湿模型及应用

利用封套对装备进行集合封存具有轻便、廉价、可靠等优点,它可建立一个阻隔封存环境以解决野战条件下各种装备的防潮问题。通过分析封套封存环境的各种潮湿因素,建立了封套封存环境透湿模型。利用该模型对现有干燥剂用量的计算方法进行了改进。     

Development programs for one‐shot systems using multiple‐state design reliability models

Design reliability at the beginning of a product development program is typically low, and development costs can account for a large proportion of total product cost. We consider how to conduct development programs (series of tests and redesigns) for one‐shot systems (which are destroyed at first use or during testing). In rough terms, our aim is to both achieve high final design reliability and spend as little of a fixed budget as possible on development. We employ multiple‐state reliability models. Dynamic programming is used to identify a best test‐and‐redesign strategy and is shown to be presently computationally feasible for at least 5‐state models. Our analysis is flexible enough to allow for the accelerated stress testing needed in the case of ultra‐high reliability requirements, where testing otherwise provides little information on design reliability change. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Properties of some stochastic orders: A unified study

The notions of the likelihood ratio order of degree s (s ≥ 0) are introduced for both continuous and discrete integer‐valued random variables. The new orders for s = 0, 1, and 2 correspond to the likelihood ratio, hazard rate, and mean residual life orders. We obtain some basic properties of the new orders and their up shifted stochastic orders, and derive some closure properties of them. Such a study is meaningful because it throws an important light on the understanding of the properties of the likelihood ratio, hazard rate, and mean residual life orders. On the other hand, the properties of the new orders have potential applications. © 2003 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

基于MapGIS的突发事件应急指挥系统设计与实现

针对当前突发事件处理过程中人为因素过多,容易出现错误决策的不足,设计实现了基于MapGIS的突发事件应急指挥系统。系统包括地图操作、突发事件应急决策、突发事件模拟等功能,并以应急决策模块为例说明了系统实现。     

基于种群多样性测度的PSO算法及其应用研究

针对基本粒子群算法(particle swarm optimization,PSO)易局部收敛的缺陷,设计了一种根据种群多样性测度动态调整惯性权重的改进粒子群算法,通过仿真测试函数与基本粒子群算法、自适应粒子群算法(adaptive particle swarm optimization,APSO)、带收缩因子的粒子群算法(contractive particle swarm optimization,CPSO)进行比较,改进的PSO算法在提高算法的综合搜索能力方面具有优越性。将改进的PSO算法运用到作战飞行器航迹规划中,并进行了仿真实验,仿真结果验证了改进算法的有效性。