Investigations on temperature distribution of satellite surfaces affected by solar absorptivity

Based on the Monte Carlo ray-tracing method, the network coefficients of thermal network model describing the radiation heat transfer among satellite surfaces is solved by considering the surface material optical characters. It is superiority to the conventional Gebhart’s method in view of the grey body and the diffuse reflection assumptions. The zone leveling method is used to discrete the governing equations and the solar absorpivity is separated and considered to be an important correction parameter. Effects of the solar incidence round angle, the zenith angle and the ratio of absorpivity to emissivity (RAE) on temperature distribution are numerically simulated and discussed in detail. The higher or the lower the RAE may be lead to the alternative heating and cooling tend with a larger heating or cooling velocity of main body surfaces than the solar array surfaces. Furthermore, maximum temperature of main body is almost larger than solar arrays. Under the same RAE, solar incidence angle make a great effect on the uniform character of temperature distribution.     

一种RapidIO交换网络配置方法的设计与实现

RapidIO技术主要面向高性能的嵌入式系统互连通信,具有比以太网、PCIE更高的传输效率,能够为嵌入式系统提供一种可靠、有效的互连通信。介绍了RapidIO网络的组成以及交换的基本原理及RapidIO交换网络的配置方法,并且通过实例分析,实现了RapidIO交换网络的配置。     

高精度星敏感器热设计研究及仿真验证

为实现某高精度星敏感器在空间复杂热环境下的可靠应用,对该星敏感器的热设计进行了分析研究,并选取典型的高温工况和低温工况进行讨论。基于热网络模型对高温工况和低温工况计算及仿真分析,提出了星敏感器与卫星舱体在导热和隔热2种安装情况下的热控措施。分析结果表明:当星敏感器导热安装时,将安装面温度控制在-15～0℃,在其外表面包覆多层隔热组件,可使整机温度适宜;当星敏感器隔热安装时,在其盖板外表面喷涂热控白漆,将遮光罩与盒体隔热安装,设置用于温度补偿的电加热片,将安装面温度控制在-60～-30℃。     

基于BiSNet的航天发动机转子智能健康监控

航天发动机某部件转子健康监控,对检测发动机能否正常工作进而影响航天发射任务的成败至关重要。传统健康监控方法需要依赖经验和专业知识,在对故障机理深入理解后才能构建相应的健康监控模型。针对传统转子健康监控手段效率低、适应性差、过度依赖专家经验等不足,结合海量转子振动健康监控历史数据,提出并设计采用神经网络BiSNet的人工智能方法,对航天领域运载火箭发动机某部件转子的健康状态进行智能建模并完成监控。通过与传统监控手段和主流基准神经网络方式对照实验得出结论,基于历史数据驱动的神经网络BiSNet可为航天转子智能健康监控提供便捷准确的建模预测。     

基于NIRGAM的片上网络性能仿真

采用虫孔交换和虚拟通道技术的片上网络系统(NoC)能极大地降低传输延时,防止微片拥塞,增大网络吞吐率,从体系结构上解决了总线通信技术的瓶颈。片上网络的虚拟通道由多个缓冲区组成,其数目直接影响芯片的面积,必须通过仿真得到面积和缓冲区数目的平衡。使用NIRGAM仿真器对不同缓冲区数目的 2D Mesh片上网络进行了仿真,对其源代码中几个重要参数提出了修改建议,仿真结果表明,在本文配置的通信情况下缓冲区深度为4微片时NoC系统整体性能最好。     

使用Trimble Geomatics Office等商业随机软件应注意的几个问题

通过对Trimble Geomatics Office等随机软件的实际应用,提出一些数据质量控制措施.根据随机软件网平差功能的特点,通过对所有基线网和独立基线网的对比分析,得出选择独立基线网平差更合理、测量结果更可靠的结论.     

Model-free adaptive optimal design for trajectory tracking control of rocket-powered vehicle

An adaptive optimal trajectory tracking controller is presented for the Solid-Rocket-Powered Vehicle (SRPV) with uncertain nonlinear non-affine dynamics in the framework of adaptive dynamic programming. First, considering that the ascent model of the SRPV is non-affine, a model-free Single Network Adaptive Critic (SNAC) method is developed based on the dynamic neural network and the traditional SNAC method. This developed model-free SNAC method overcomes the limitation of the traditional SNAC method that can only be applied to affine systems. Then, a closed-form adaptive optimal controller is designed for the non-affine dynamics of SRPVs. This controller can adjust its parameters under different flight conditions and converge to the approximate optimal controller through online self-learning. Finally, the convergence to the approximate optimal controller is proved. The theoretical analysis of the uniformly ultimate boundedness of the tracking error is also presented. Simulation results demonstrate the effectiveness of the proposed controller.     

风洞无线智能传感器网络及无线测量技术研究

风洞试验现场，特别是大型连续式风洞试验现场的电磁环境非常恶劣，而风洞实验中的测量信号又是毫伏级的微弱信号，采用传统测量方式难以克服恶劣的电磁环境对测量系统的干扰。对于运动物体或无法布线的试验环境进行参数测量时，传统测量方式完全不起作用。针对上述问题，笔者对风洞无线智能传感器网络和无线测量技术进行了研究，采用ZIGBEE技术实现了风洞无线智能传感器网络和基于该网络的无线测量模块。极大地增强了测量系统的抗干扰能力，提高了风洞试验的精细化程度，降低了测量系统的经济成本。     

一种新的基于双控制信道Ad Hoc网络媒体接入控制协议

提出了一种新的基于双控制信道的AdHoc网络媒体接入控制(MAC)协议。该协议在两个相互正交的子信道上交换RTS/CTS控制分组,解决了RTS丢失问题、死锁问题以及多信道隐藏终端问题,并提高了协议的空间复用度。实验结果表明,和已有的多信道的接入协议相比,在网络负载较重和节点密度较大的情况下,新协议提高了网络的吞吐量。     

Modeling and Algorithm Application of Weapon Assignment System

In order to improve weapon assignment(WA)accuracy in real scenario,an artificial neural network(ANN)model is built to calculate real-time weapon kill probabilities.Considering the WA characteristic,each input representing one assessment index should be normalized properly.Therefore,the modified WA model is oriented from constant value to dynamic computation.Then an improved invasive weed optimization algorithm is applied to solve the WA problem.During search process,local search is used to improve the initial population,and seed reproduction is redefined to guarantee the mutation from multipoint to single point.In addition,the idea of vaccination and immune selection in biology is added into optimization process.Finally,simulation results verify the model′s rationality and effectiveness of the proposed algorithm.