Stewart平台远程操作试验系统的研制

为了研究Stewart平台大时延情况下的远程操作稳定性,建立了相关试验系统.用以太网模拟远程通信信道,连接2套Stewart平台控制系统;利用DirectX技术,对用户屏蔽了具体硬件设备,建立了用户输入接口和视频反馈;利用OpenGL(Open Graphic Library)技术,建立了虚拟操作环境,以便于未来利用虚拟操作环境补偿时延;用神经网络的位置正解方法代替传统方法驱动虚拟模型,获得更高的精度;对通讯的带宽进行在线监控,优先保证指令传输;通过改变发送速率,保证视频连续发送.试验结果表明,用户通过输入指令可以方便地控制平台,平台位姿可以通过虚拟操作环境和视频进行反馈,系统满足了设计要求.      

虚拟作战系统的演化建模研究

提出虚拟作战系统演化模型的内涵、研究目的与目标;研究了虚拟作战系统仿真原理与建模过程以及演化建模方法,提出了基于主体的虚拟作战系统演化建模方法;设计了虚拟作战系统演化模型体系结构,总结了虚拟作战系统模型的组合层次,并给出了模型间的信息控制关系。     

“做中教”教学法在高职教学中的应用

阐述“教学做合一”教育思想的精髓及其教学观的主要内涵,论述高职教育应以实践教学为中心,教师在教学中应学会在“做中教”,努力达到“教学做合一”。     

空天一体作战C4I系统效能研究

根据空天一体作战指挥控制系统结构特点,建立了关于C4I系统的结构模型和指挥控制系统的逻辑模型,分析了该模型对未来空天作战的影响。在建立的网络结构模型的基础上,建立了编队攻击网络机构模型。运用梅特卡夫定律和组合数学相结合建立评估编队能力指数的评价标准。该算法与实际作战相结合,能较好地量化作战编队的作战效能。     

甚高频空地数据链的通信链接控制模式分析

通信链接控制模式与甚高频 ( VHF)空地数据链的性能、系统容量和系统冗余度密切相关,采用嵌入式马尔可夫模型,详细分析了目前正在使用的两种典型的通信链接控制模式对空地数据链性能的影响,进行了计算机仿真,对分析结果进行了比较研究,并以此提出一种有效的新型通信链接控制模式。     

家庭安全监控的实时异常检测与分类算法

同时具有好的实时性和稳健性是基于视频的安全监控系统异常检测算法的难点问题.在家庭安全监控系统中同时利用像素的亮度分量和色度分量检测变化像素,解决摄像镜头由于大尺寸对象闯入引起的图像背景变化造成运动对象检测失败的问题;提出一种实时运动对象分类算法,综合利用开关灯检测、运动距离分析和皮肤探测多种方法,区分是否出现影响家庭安全的事件;提出3关键值背景维护算法,用于消除背景振动像素,减少虚假报警.实验表明,本文异常探测算法对视频监控系统异常探测和消除虚假异常报警具有较好的实时性和稳健性.      

Delphi与C++语言编程特点之比较

通过与功能强大的C语言比较,系统地介绍和总结了Delphi所采用语系Object Pascal中丰富的指针操作、位运算和编译预处理的特点和用法,用于指导Delphi程序员编写高质量的应用软件。     

Robust leaderless time-varying formation control for unmanned aerial vehicle swarm system with Lipschitz nonlinear dynamics and directed switching topologies

This paper tackles the robust leaderless Time-Varying Formation(TVF) control problem for the Unmanned Aerial Vehicle(UAV) swarm system with Lipschitz nonlinear dynamics, external disturbances and directed switching topologies. In comparison with the previous achievements on formation control problems, the UAV swarm system with Lipschitz nonlinear dynamics can accomplish the pre-designed TVF while tracking a pre-given trajectory which is produced by a virtual leader UAV in the presence of externa...     

Neural network prediction of the topside electron content over the Euro-African sector derived from Swarm-A measurements

This study presents the first prediction results of a neural network model for the vertical total electron content of the topside ionosphere based on Swarm-A measurements. The model was trained on 5 years of Swarm-A data over the Euro-African sector spanning the period 1 January 2014 to 31 December 2018. The Swarm-A data was combined with solar and geomagnetic indices to train the NN model. The Swarm-A data of 1 January to 30 September 2019 was used to test the performance of the neural network. The data was divided into two main categories: most quiet and most disturbed days of each month. Each category was subdivided into two sub-categories according to the Swarm-A trajectory i.e. whether it was ascending or descending in order to accommodate the change in local time when the satellite traverses the poles. Four pairs of neural network models were implemented, the first of each pair having one hidden layer, and the second of each pair having two hidden layers, for the following cases: 1) quiet day-ascending, 2) quiet day-descending, 3) disturbed day-ascending, and 4) disturbed day-descending. The topside vertical total electron content predicted by the neural network models compared well with the measurements by Swarm-A. The model that performed best was the one hidden layer model in the case of quiet days for descending trajectories, with RMSE = 1.20 TECU, R = 0.76. The worst performance occurred during the disturbed descending trajectories where the one hidden layer model had the worst RMSE = 2.12 TECU, (R = 0.54), and the two hidden layer model had the worst correlation coefficient R = 0.47 (RMSE = 1.57).In all cases, the neural network models performed better than the IRI2016 model in predicting the topside total electron content. The NN models presented here is the first such attempt at comparing NN models for the topside VTEC based on Swarm-A measurements.     

直升机/舰船耦合流场的数值模拟

发展了一套基于雷诺平均Navier-Stokes(RANS)方程的直升机/舰船耦合流场数值模拟方法,采用ROEMUSCL格式对交接面通量进行重构,并采用k-ε湍流模型以提高对涡流场的捕捉精度,直升机旋翼等旋转部件的模拟使用动量源模型。然后,以具有典型驱护舰结构的LPD-17及ROBIN直升机的组合为研究对象,从涡量场、速度场及压力场等方面分析了直升机、舰船耦合情形下的流场特征。研究表明,当来流速度V_∞≥4m/s时,舰船流场进入雷诺数自准区,流场速度无因次化量基本保持不变;直升机着舰时,旋翼会与舰船艉部的涡回流区以及甲板两侧的舷涡发生较强的"涡-涡干扰",在上述干扰以及舰面效应的共同作用下,旋翼拉力产生显著的振荡,并呈现出先减小、后增大的变化特征;当着舰位置向舰尾移动时,艉部回流区的影响减弱,旋翼拉力振荡幅度相应减小。最后,对全机状态下的耦合流场进行了模拟,结果显示机身和尾桨对舰艉流场的主要结构影响较小,可用旋翼/舰船耦合流场来进行直升机安全着舰分析,这将显著缩短计算时间。