A fast-running method for blast load prediction shielding by a protective barrier

This study presents a simplified blast load prediction method on structures behind a protective barrier. The proposed method is basically an empirical approach based on Kingery-Bulamsh (K-B) chart and finite element (FE) analysis results. To this end, this study divides the structure into three regions by three critical points. Blast loads at each critical point can be calculated based on K-B chart and an approximation according to FE analysis results. Finally, peak reflected overpressure and impulse distributed on the structure can be approximately estimated by linearly connecting blast loads at each critical point. In order to confirm a feasibility of the proposed method, a series of numerical simulations were carried out. The simulation results were compared with FE analysis results which are presented in the open literature. From such comparisons, it was found that the proposed method is applicable to predict blast loads on structures behind a protective barrier.     

3D laser scanning strategy based on cascaded deep neural network

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s. The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.     

基于多信号模型的装甲车辆电源系统诊断策略

针对装甲车辆电源系统模块失效和信号失效不统一的特点,提出了一种多信号模型的改进方法,在此基础上,通过电源系统故障模式影响分析,建立了电源系统测试性模型。基于故障熵理论,利用诊断信息量和费用优化的启发式函数,确立了系统的诊断策略。计算结果表明:该方法对诊断策略的优化是有效的。该方法对装甲车辆电源系统诊断策略的研究具有一定参考意义。     

一维三体碰撞过程的数值实验研究

力学中常常将物体之间的相互作用描述为碰撞过程,两体碰撞模型广泛地运用于处理各种物理问题,然而现实世界中普遍存在着多体碰撞.文中建立了三体碰撞过程的动力学方程组,对一维完全弹性三体碰撞进行了数值实验研究.研究结果表明,三体碰撞物体的分离速度与物体之间相互作用过程的细节有关,一般情况下不能简化为相继的两次两体碰撞求解.     

高可靠性软件的极值统计分析

提出了极值统计分析的方法.对于失效数据极值分布函数的拟合检验,采用了相关系数法;对于母体分布的参数估计,则分别采用了最小二乘估计(LSE)和极大似然估计(MLE);最后通过一个实例说明了统计过程,并用模拟的方法证明了最小二乘估计较好.     

由路面谱重构路面不平度的AR模型法

将等级路面的不平度视为一零均值的噪声序列通过一个AR模型产生的随机序列,通过求解Yule-Walker方程得出AR模型参数,进而得到路面不平度。经数值算例构造出4个等级的路面不平度,验证了用AR模型构造路面不平度方法的可行性与可靠性。     

箱装物资装运模型的构建及提货可视化设计

以汽车为例介绍了物资装载时横装、顺装和混装等几种模型,并对其算法进行了归纳。设想了一个以物资出入库为原型的可视化系统,并以建立的装运模型为基础,设计了可视化提货系统的实现过程。     

新型船用气体稳压器启动充气过程的建模及仿真研究

基于船用核动力一体化反应堆结构的需要,建立了新型船用气体稳压器启动充气过程的数学模型,并进行了仿真计算.计算结果表明,该模型能正确地描述该型稳压器实际的启动充气过程,满足工程设计及系统研究的需要.     

基于威布尔过程模型的坦克部署期可靠性研究

通过对某新研坦克部署期故障情况进行具体而全面的统计分析,并采用基于随机点过程的可修系统理论中的威布尔过程模型(AMSAA模型),得出该型坦克部署期的可靠性特点与规律,对于研究新装备可靠性规律和提高新装备的部署保障水平,具有重要的借鉴作用.     

钝感弹药引爆模型研究

介绍了钝感弹药的概念。概述了与钝感弹药密切相关的新型引爆系统。阐明了新型引爆系统用于钝感弹药的必要性和可行性。该系统对推进钝感弹药引爆技术,特别是高新技术弹药的发展有重要意义。