液体远地点发动机工作期间卫星姿态的自适应控制

本文将全系数自适应控制方法用于带有液体晃动和挠性太阳帆板的三轴稳定地球同步轨道卫星在远地点发动机工作期间的姿态自适应控制。仿真结果表明,用全系数自适应控制方法设计的控制器,其动态性能好,对参数变化的适应性强,抗干扰能力强,鲁棒性好,性能指标完全满足设计要求。     

黄金分割自适应鲁棒控制器设计新方法

本文在全系数自适应控制理论基础上,给出了一种实用的黄金分割自适应鲁棒控制器的设计方法及理论分析。对于参数未知、线性定常或慢变的二阶对象,只要参数估计值在一个范围内,该控制器就能保证闭环系统稳定,且系统输出的动态性能较好。从而解决了二阶系统自适应控制在初始过渡过程阶段的实际应用问题。     

预应力过载对低周疲劳及da/dN的影响

研究了预拉伸应力过载对TC-11钛合金及GH33A高温合金的低周疲劳及da/dN的影响。证明在5×10~3～5×10~4低周疲劳寿命范围内,单边缺口试样的疲劳裂纹起始寿命Ni有明显提高,并可用经验表达式S~m(N_f/r)=C来估算,但对其裂纹扩展寿命Np的影响则并不显著。     

固体发动机失效树定量分析法

根据固体火箭发动机失效树定量分析中确定底事件失效概率存在的困难,提出了确定底事件失效概率的工程方法——征求意见评分法。通过对某型号发动机试样阶段结构可靠性实例分析,得出了较满意的结果。     

DA4169合金高温疲劳裂纹扩展速率

实验研究了直接时效ＤＡ４１６９合金５５０℃、６５０℃下的疲劳裂纹扩展行为，并进行了带上峰值保持时间的试验。结果表明：连续循环的ｄａ／ｄＮ值基本上与普通４１６９的相当，但在６５０℃下略优；６５０℃带上峰值保时１５ｓ的ｄａ／ｄＮ值比连续循环的大大加速。     

红外隐身材料的现状与展望

综述了国内外红外隐身材料的发展历程，重点介绍了构成红外隐身材料的填料、树脂的研究现状以及近年来开始重点研究的红外兼容型多频谱隐身材料，并且指出了红外隐身材料的发展方向。     

一种定向凝固高温合金低周疲劳性能的研究

研究了同成分合金在定向凝固（ＤＳ）和普通铸造（ＣＣ）状态下７６０℃的低周疲劳性能。结果表明，ＤＳ合金的疲劳寿命比ＣＣ合金在应力控制条件下高２倍左右，而在应变控制条件下可提高寿命２０倍左右。ＣＣ合金的疲劳裂纹往往萌生在与表面相连的晶界或某些缺陷（如孔洞）上，由外向内沿晶界扩展。而ＤＳ合金裂纹则起源于纵向晶界的横段或预开裂的碳化物，并沿枝晶间穿枝干扩展。     

舱门机构运动的计算机模拟

1.构造及其原始数据 滑轨舱门收放机构由中、侧滑轨、三角支架、外伸臂、链条条、链轮、液压马达及减速装置等组成(图1)。一根中滑轨布置在43框前飞机对称平面内与飞机外形的下零纵线相贴合,两根侧滑轨分别布置在43框后机身的两侧,舱门的前端由一个接头铰支在三角支架上,三角支架的前支点与链条相连,舱门的后部和两个外伸臂固接,     

细长体分离起始点的实验研究

本文实验研究了细长体模型在中等迎角下的初始分离问题。观察了不同头部形状的细长体在不同迎角下的分离流态。考察并分析了分离起始点的性质。观察到开式分离的存在,实验结果分析认为开式分离可以起始于正常点。此外,在钝头和尖头模型上都出现了螺旋点形式的头部涡。它们或是闭式分离的起始点,或是奇点型开式分离的起始点。     

Detection of small objects in clutter using a GA-RBF neural network

Detection of small objects in a radar or satellite image is an important problem with many applications. Due to a recent discovery that sea clutter, the electromagnetic wave backscatter from a sea surface, is chaotic rather than purely random, computational intelligence techniques such as neural networks have been applied to reconstruct the chaotic dynamic of sea clutter. The reconstructed sea clutter dynamical system which usually takes the form of a nonlinear predictor does not only provide a model of the sea scattering phenomenon, but it can also be used to detect the existence of small targets such as fishing boats and small fragments of icebergs by observing abrupt changes in the prediction error. We applied a genetic algorithm (GA) to obtain an optimal reconstruction of sea clutter dynamic based on a radial basis function (RBF) neural network. This GA-RBF uses a hybrid approach that employes a GA to search for the optimum values of the following RBF parameters: centers, variance, and number of hidden nodes, and uses the least square method to determine the weights. It is shown here that if the functional form of an unknown nonlinear dynamical system can be represented exactly using an RBF net (i.e., no approximation error), this GA-RBF approach can reconstruct the exact dynamic from its time series measurements. In addition to the improved accuracy in modeling sea clutter dynamic, the GA-RBF is also shown to enhance the detectability of small objects embedded in the sea. Using real-life radar data that are collected in the east coast of Canada by two different radar systems: a ground-based radar and a satellite equipped with synthetic aperture radar (SAR), we show that the GA-RBF network is a reliable detector for small surface targets in various sea conditions and is practical for real-life search and rescue, navigation, and surveillance applications