基于贝叶斯网络的自动装弹机维修决策

在分析贝叶斯网络的结构和特点的基础上,以自动装弹机的部件输弹机为例,构建了输弹机不旋转故障模式的贝叶斯网络模型,并对网络模型进行训练和学习,在计算网络模型相关参数的基础上进行维修决策分析,梳理出排除输弹机不旋转故障的一般性方法,为研究自动装弹机的维修决策提供参考。     

压制性干扰对地空导弹搜索雷达侦察效能的建模

为了提高地空导弹在复杂电磁环境下的作战能力,从雷达工作原理及电子干扰机理的分析入手,建立了相关数学模型,并就压制性干扰对地空导弹搜索雷达侦察效能的影响进行了定量计算分析。通过分析计算结果,得出一些有重要意义的结论,对提高地空导弹搜索雷达的抗干扰能力具有借鉴意义。     

基于服务的炮兵通信网络资源管理研究

在分析炮兵通信网络资源现状及资源管理需求基础上,从网络资源池的构建与管理、网络资源的组件与封装、资源池内的组件组合与调度3个方面提出了基于服务的炮兵通信网络资源管理方法,此方法实现了网络资源的"纵向扁平化、横向一体化"管理,使资源管理与网络结构、作战指挥结构松耦合,便于网络资源柔性扩展以及弹性服务的提供,为联合作战条件下,面向多军兵种资源融合与信息共享的统一通信服务实施提供技术借鉴与支撑。     

基于雷达网拓扑特征的雷达目标编群算法

为有效评估战场电磁态势和实施雷达网对抗,研究雷达目标编群算法十分必要。提出了一种基于拓扑特征分析的雷达目标编群算法,在分析雷达网拓扑结构及其特征基础上,利用拓扑特征实现雷达目标群的建立和更新,完成雷达目标编群。仿真实例表明算法具有可行性和有效性,为电磁态势评估和雷达网对抗奠定了基础。     

受互联网思路启发的电力系统重要节点评估算法

对电力系统中重要节点进行有效区分,有助于在资源有限的条件下对重要节点施加额外保护或改变拓扑结构,从而提高系统鲁棒性、降低事故发生的概率。受网页排序算法启发,提出电气链接结构分析的随机方法(electrical stochastic approach for link structure analysis, E-SALSA)用于电力系统重要节点评估。该算法综合考虑了电力系统拓扑结构、潮流等因素对节点的影响,能够有效反映电力系统的真实情况,并且其特点更符合电力系统背景。在IEEE300节点电力系统中,使用失负荷规模和最大子群规模两个指标对E-SALSA算法与电气介数算法、基于共同引用的超链接引导的主题搜索(model based on co-citation hypertext induced topic search, MBCC-HITS)算法进行了对比分析。结果证明E-SALSA算法相比电气介数算法在两个指标上都具有优势,相比MBCC-HITS算法能够更综合考虑各方面因素对节点的影响,进而证明了E-SALSA算法的合理性、有效性。     

基于CNN的三相逆变器开路故障诊断及其样本条件分析

为了合理选择样本条件以实现高效的智能化诊断,以及克服智能化方法中传统反向传播(back propagation, BP)网络权值较多、局部信息提取能力不足的问题,对基于卷积神经网络(convolutional neural network, CNN)的开路故障诊断方法进行研究,并以典型的三相两电平逆变器为具体对象,着重分析样本时长、样本数量变化时,CNN方法相较于BP网络方法在网络权值数量、训练稳定性、诊断准确率上的量化优势。结果表明,基于CNN的方法可在权值数量远少于BP网络方法的情况下构建深度更深的诊断模型,并在更短样本时长、更少训练样本数量下实现高效、准确的开路故障诊断。     

Data-driven prediction of plate velocities and plate deformation of explosive reactive armor

Explosive reactive armor (ERA) is currently being actively developed as a protective system for mobile devices against ballistic threats such as kinetic energy penetrators and shaped-charge jets. Considering mobility, the aim is to design a protection system with a minimal amount of required mass. The efficiency of an ERA is sensitive to the impact position and the timing of the detonation. Therefore, different designs have to be tested for several impact scenarios to identify the best design. Since analytical models are not predicting the behavior of the ERA accurately enough and experiments, as well as numerical simulations, are too time-consuming, a data-driven model to estimate the displacements and deformation of plates of an ERA system is proposed here. The ground truth for the artificial neural network (ANN) is numerical simulation results that are validated with experiments. The ANN approximates the plate positions for different materials, plate sizes, and detonation point positions with sufficient accuracy in real-time. In a future investigation, the results from the model can be used to estimate the interaction of the ERA with a given threat. Then, a measure for the effectiveness of an ERA can be calculated. Finally, an optimal ERA can be designed and analyzed for any possible impact scenario in negligible time.     

A pixel-level local contrast measure for infrared small target detection

Infrared (IR) small target detection is one of the key technologies of infrared search and track (IRST) systems. Existing methods have some limitations in detection performance, especially when the target size is irregular or the background is complex. In this paper, we propose a pixel-level local contrast measure (PLLCM), which can subdivide small targets and backgrounds at pixel level simultaneously. With pixel-level segmentation, the difference between the target and the background becomes more obvious, which helps to improve the detection performance. First, we design a multiscale sliding window to quickly extract candidate target pixels. Then, a local window based on random walker (RW) is designed for pixel-level target segmentation. After that, PLLCM incorporating probability weights and scale constraints is proposed to accurately measure local contrast and suppress various types of background interference. Finally, an adaptive threshold operation is applied to separate the target from the PLLCM enhanced map. Experimental results show that the proposed method has a higher detection rate and a lower false alarm rate than the baseline algorithms, while achieving a high speed.     

基于DEA方法的新疆少数民族高等教育效率评价研究

由于数据包络分析方法（DEA）对多输入多输出系统的效率评价问题具有十分独特的优势。近年来,DEA方法在高等教育效率评价,尤其是在高等学校人力资源利用效率评价中的应用日趋增多,取得了丰硕的研究成果。本文针对新疆少数民族高等教育效率评价问题,重点从地域角度,采用DEA交叉评价方法定量研究新疆少数民族高等教育资源利用效率的状况,以期为教育管理者在制定资源配置政策以及高校在如何提高资源利用效率方面提供借鉴与参考。     

以优质的信息服务打造武警高校名牌图书馆

武警院校图书馆要以提供优质的信息服务为着眼点,不断创新服务理念、服务方法和服务手段,并通过各项措施保障优质信息服务,达到创建武警高校名牌图书馆的目的。