Perspective on space radiation for space flights in 2020–2040

The Sun undergoes several well known periodicities in activity, such as the Schwabe 11 year cycle, the Gleissberg 80–90 year cycle, the Suess 200–210 year cycle and the Halstatt 2200–2300 year cycle. In addition, there is evidence that the 20th century levels of solar activity are unusually high. The years 2020–2040 are expected to coincide with increased activity in human space flight beyond low Earth orbit. The solar cycles and the present level of solar activity are reviewed and their activities during the years 2020–2040 are discussed with a perspective on space radiation and the future program of space flight. It is prudent to prepare for continuing levels of high solar activity as well as for the low levels of the current deep minimum, which has corresponded to high galactic cosmic ray flux.     

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast. Thus safety of aircraft taking off and landing and air flight can be guaranteed. Thresholding is a kind of simple and effective method of cloud classification. It can realize automated ground-based cloud detection and cloudage observation. The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect. Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation. In view of the above-mentioned problems, multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization （UPSO） are proposed. Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy. In addition, exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster. Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy. In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection, the UPSO algorithm is adopted. It can find the optimal thresholds quickly and accurately. As a result, the real-time processing of segmentation of groundbased cloud image can be realized. The experimental results show that, in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy, the proposed methods can extract the boundary shape, textures and details feature of cloud more clearly. Therefore, the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.     

基于闭环准则的LQG/LTR飞行控制律优化设计

针对LQG/LTR飞行控制律设计中加权矩阵的选取问题,提出了一种基于闭环准则的LQG/LTR飞行控制律优化设计方法。以俯仰姿态控制律优化设计为例,首先基于闭环准则选取了满足一级飞行品质要求的参考模型,并基于该参考模型使用粒子群优化算法优化得到了两个加权矩阵,从而得到了卡尔曼滤波器和相应的目标反馈回路。进而借鉴飞机等效系统拟配的方法,优化得到了另两个加权矩阵,从而得到了LQG最优控制器,完成了回路传递恢复的优化设计。仿真结果表明,通过该方法能够快速自动地选取合适的加权矩阵,使得优化设计的LQG/LTR飞行控制律较好地满足了俯仰姿态控制的要求。     

SiCP/Al复合材料棱镜组件研磨工艺方法研究

通过对SiCp/Al复合材料棱镜组件研磨工艺试验及其结果分析,总结、优化了研磨工艺参数、研磨砂种类、粒度、研磨时间、研磨工艺过程等参数,研磨出的棱镜组件符合其精度要求,为棱镜组件在平台上的安装精度提供了基础.     

连续变速颤振试验的自适应粒子滤波算法

连续变速颤振试验的采集信号通常为非平稳信号,其频率和幅值随时间变化,尤其在亚临界状态下, 变化程度十分剧烈。常用的非平稳信号时变参数建模分析方法,在信号非平稳程度较高的情况下难以对信号 的模态进行准确地分析和跟踪。为了解决这一问题,结合信号非平稳度量计算方法,提出一种改进的自适应粒 子滤波算法,并通过仿真实验数据对所提算法在高非平稳度情况下的跟踪性能进行验证。结果表明:与一般粒 子滤波算法相比,本文方法在高非平稳度情况下具有更高的跟踪精度。     

应用粒子激光散射测量混合反应器分散相浓度场分布

研究了圆管反应器中四束侧向对撞射流与轴向流形成的混合流动.应用激光粒子散射成像测量了侧向分散相在混合流中的浓度场分布,得到了不同的浓度分布图形随侧向流与轴向流速比关系,揭示了内在有规律的独特的浓度分布结构.     

PIV诊断系统在Mac机上的移植与改进

实现粒子图像测速（PIV）包括两个关键步骤：粒子图像的获取和粒子图像的处理。本文为粒子图像的处理探索出了一条新的途径，实现了原诊断系统在Mac机上的移植，并且根据Mac机处理图像信息的先进性对原处理系统进行了改进，特别增强了其后处理功能。     

自由漂浮空间机器人最小基座反作用轨迹规划

在自由漂浮空间机器人系统中,由于机械臂与基座之间存在动力学耦合,机械臂运动会对基座产生不期望的反作用干扰,因此必须最小化基座反作用。为此,提出了一种关节空间内点对点轨迹规划的方法。首先,利用sin函数参数化关节轨迹;然后根据基座反作用和运动约束定义适应函数;最后利用混沌粒子群优化(CPSO)算法搜索空间机械臂的全局最优轨迹,使基座反作用最小。该方法考虑了机械臂的关节角、关节速度和加速度约束。给出一个仿真算例来验证该方法的有效性。规划的轨迹连续平滑,适用于多自由度空间机械臂。     

基于复合优化的航空发动机模型参数估计

本文提出了一种复合优化方法,用于发动机多变量,状态空间模型的时域辨识。优化中粒子群优化算法和最小二乘优化算法按照“串联”方式运行。粒子群优化从一个初始种群出发,通过进化来搜索最优解。然而有些时候,粒子群算法会陷入次优解。那么最小二乘优化算法就可以从粒子群的次优解出发,通过共轭梯度法获得问题的最优解。本方法适用于待估计参数较多,且参数变化范围大的高阶多变量系统。本文将复合优化算法用于4输入4输出状态变量模型参数的估计。仿真结果表明了所提出方法的有效性。     

基于改进支持向量机的模拟电路故障诊断研究

针对支持向量机（Support Vector Machine）及小波分解用于模拟电路故障诊断时,一对一算法具有操作简单、诊断精度高、所需确定参数少,小波分解能表现电路响应特征但最优小波基选取目前缺乏有效方法的特点,提出利用混合粒子群算法（Hybrid Particle Swarm Optimization,HPSO）对小波基及一对一支持向量机的参数进行联合优化。将该方法应用于模拟滤波器的仿真电路实验,结果表明：利用该方法很容易求出全局最优解,能实现对最优小波基选取及支持向量机参数进行联合优化,避免了参数选择的盲目性,提高了模型的诊断精度。