一类非线性脉冲时滞抛物型偏微分方程组解的振动性

讨论了一类含脉冲的时滞抛物型方程组非零解的振动性,利用了Green定理以及Jensen不等式,得出了该方程在Robin边界条件下非零解振动的若干准则。     

基于粗糙集的装备维修信息属性约简算法

分析了装备维修信息的概念和组成,将粗糙集理论应用到装备维修信息处理中,结合信息熵和互信息的定义,界定了一种新的属性重要度,并将其作为启发信息,提出了改进的基于属性重要度和互信息的属性约简算法,并通过对装备维修信息约简,进行了算法验证。实验结果表明:所提出的算法精度较高,得到的结果比较符合实际,能够为装备维修保障提供决策依据。     

战场环境下无人车辆战术机动路径规划方法

针对不同类型威胁体存在的战场环境中无人车辆战术机动路径规划问题,提出了一种基于威胁代价地图的粒子群优化（Particle Swarm Optimization,PSO）方法。借助极坐标系中关键点的极角进行路径描述,并使用分段3次Hermite插值方法形成光滑路径,将路径规划问题转化为关键点极角的参数优化问题。针对基本PSO（BPSO）算法存在的早熟收敛和后期迭代效率低的缺陷,借鉴以群集方式生活的物种按照不同任务对种群进行分工的机制,提出了一种基于多任务子群协同的改进粒子群优化（Particle Swarm Optimization based on the Multi—tasking Subpopu—lation Cooperation,PSO-MSC）算法。借助该算法的快速收敛和全局寻优特性实现了最优路径规划。实验结果表明：该算法可以快速有效地实现战场环境下无人车辆的战术机动路径规划,且规划路径安全、平滑。     

The effect of al particle size on thermal decomposition,mechanical strength and sensitivity of Al/ZrH2/PTFE composite

To study the thermal decomposition of Al/ZrH2/PTFE with different Al particle size as well as mechanical strength and impact sensitivity under medium and low strain rates, molding-vacuum sintering was adopted to prepare four groups of power materials and cylindrical specimens with different Al particle size. The active decomposition temperature of ZrH2 was obtained by TG-DSC, and the quasi-static me-chanics/reaction characteristics as well as the impact sensitivity of the specimen were studied respec-tively by quasi-static compression and drop-hammer test. The results show that the yield strength of the material decreased with the increase of the Al particle size, while the compressive strength, failure strain and toughness increased first and then decreased, which reached the maximum values of 116.61 MPa, 191％, and 119.9 MJ/m respectively when the Al particle size is 12—14μm because of particle size grading. The specimens with the highest strength and toughness formed circumferential open cracks and reacted partly when pressed. Those with developmental cracks formed inside did not react. It is considered that fracture of specimens first triggered initial reaction between Al and PTFE to release an amount of heat. Then ZrH2 was activated and decomposed, and participated in subsequent reaction to generate ZrC. The impact sensitivity of the specimens decreased with the increase of Al particle size.     

面向航天装备大数据的知识图谱体系

近年来,航天装备大数据平台建设已经取得了长足进步。然而,航天装备数据深层次价值仍然未被有效发掘,关键原因在于现有大数据业务数据存在无法跨专业贯通、缺乏全局数据资源智能分析及管理。知识图谱技术作为大数据时代的推理和分析利器,与航天装备大数据完成无缝对接具有天然的优势和内在动机。本文从研究面向航天装备数据知识图谱的/组织管理、关联分析、数据挖掘、知识可视化等开放式共享服务出发,通过大数据、人工智能方法挖掘航天数据的应用潜力,并引入数据化决策模型和监控体系,建立航天装备数据全息画像,实现业务数据的跨业务贯通,并提供网格化的高速检索,以求通过提升数据管理的规范化、标准化、精益化水平指导航天装备的优化和升级。     

Blast resistance evaluation of urban utility tunnel reinforced with BFRP bars

To improve corrosion-resistance of shallow-buried concrete urban utility tunnels(UUTs),basalt fiber reinforced polymer(BFRP)bars are applied to reinforce UUTs.As the UUT must have excellent survival capability under accidental explosions,a shallow-buried BFRP bars reinforced UUT(BBRU)was designed and constructed.Repetitive blast experiments were carried out on this BBRU.Dynamic responses,damage evolutions and failure styles of the BBRU under repetitive explosions were revealed.The tunnel roof is the most vulnerable component and longitudinal cracks develop along the tunnel.When the scaled distance is larger than 1.10 m/kg1/3,no cracks are observed in the experiments.When the BBRU is severely damaged,there are five cracks forming and developing along the roof.The roof is simplified as a clamped-supported one-way slab,proved by the observation that the maximum strain of the transverse bar is much larger than that of the longitudinal bar.Dynamic responses of the roof slab are predicted by dynamic Euler beam theory,which can consistently predict the roof displacement under large-scaled-distance explosion.Compared with the UUT reinforced with steel bars,the BBRU has advantages in blast resistance with smaller deflections and more evenly-distributed cracks when the scaled distance is smaller than 1.260 m/kg1/3 and the steel bars enter plastic state.Longer elastic defamation of the BFRP bars endows the UUT more excellent blast resistance under small-scaled-distance explosions.     

对流层散射无源监视系统最优布局方法

为提高对流层散射无源监视系统对辐射源的定位精度,利用改进粒子群优化算法对分布式监视节点进行最优布局设计。推导了基于电磁波方位到达角定位机制下的几何精度因子。在改进粒子群优化算法中,采用混沌理论初始化所有粒子的初始参数;通过自适应变化的惯性权重和学习因子来提高算法寻优能力;为防止粒子陷入局部最优,利用双子群机制进行寻优,并在两子群之间进行交叉变异操作,以增加粒子的多样性。仿真结果表明:相对于几种常规的布站方式,所提算法能够明显提高监视系统对辐射源的定位精度,运行时间较遍历寻优算法有所减少。     

基于AKF的AUV对接回收组合导航研究

针对自主水下机器人(Autonomous Underwater Vehicle,AUV)在回收过程中的组合导航精度问题,提出了一种改进的高斯距离迭代法及改进的自适应卡尔曼滤波算法(Adaptive Kalman Filter,AKF).基于AUV回收对接系统,研究并建立了针对惯导SINS、超短基线USBL、多普勒计程仪DVL和深度计的基于斜距的组合导航模型.通过对SINS/USBL/DVL/深度计组合导航量测信息误差特性分析,设计了改进的基于斜距的SINS/USBL/DVL/深度计组合导航模型;针对该模型突出的滤波发散问题,设计了基于滤波收敛性判据和强跟踪滤波思想改进的AKF滤波算法进行有机融合.仿真结果表明,此研究使实际AUV系统具有更高的滤波精度和可靠性.     

改进的YOLOV3算法在小目标检测中的研究与应用

战场目标的图像检测与识别对于战场监视、侦察、毁伤状态评估和火控系统研究等具有重要作用.以坦克装甲目标为研究对象,选用识别精度高、速度快的YOLOV3为基础目标检测模型,针对复杂战场环境中获取图像目标特征信息少的问题,引入多尺度特征增强结构的方法对YOLOV3模型进行改进,通过丰富特征图多样性的方式,提高模型性能.在坦克数据集上的实验结果表明,改进后的算法对于复杂战场环境下的小目标特征具有更强的敏感性,较大程度上增强了模型的识别精度.     

作战辅助决策模型设计及评估方法

作战辅助决策模型是在复杂战场态势下,辅助指挥人员科学、高效决策的重要工具.针对当前辅助决策模型功能分散、可信性不足、缺乏工程化设计与管理等问题,从系统工程角度出发,开展作战辅助决策模型构建与评估通用方法的研究,提出辅助决策模型工程化设计与评估分级的一般流程与方法,并结合实例进行说明.