高能固体推进剂技术未来发展展望

在分析研究现代固体推进剂技术发展的基础上,归纳总结了固体推进剂技术的发展规律及技术创新本质。结合国外发展现状,提出了高能固体推进剂技术未来发展的主要方向及重点。     

BPSK调制器发射时延的一种高精度标定方法

在高精度卫星测控、导航定位等领域,系统设备的绝对时延是影响精度的主要因素之一。示波器方案是目前能够测量BPSK调制器调制信号输入端到射频信号输出端的时延的唯一方法。文章提出采用宽带数字存储示波器结合包络检测信号处理技术,以提高调制器时延测量的精度,标准不确定度可优于50ps,避免了手工测试的主观不确定性。该方法也可推广用于变频器时延的精确测量。     

Image Smearing Modeling and Verification for Strapdown Star Sensor

To further extend study on celestial attitude determination with strapdown star sensor from static into dynamic field, one prerequisite is to generate precise dynamic simulating star maps. First a neat analytical solution of the smearing trajectory caused by spacecraft attitude maneuver is deduced successfully, whose parameters cover the geometric size of optics, three-axis angular velocities and CCD integral time. Then for the first time the mathematical law and method are discovered about how to synthesize the two formulae of smearing trajectory and the static Gaussian distribution function (GDF) model, the key of which is a line integral with regard to the static GDF attenuated by a factor 1/ L s (L s is the arc length of the smearing trajectory) along the smearing trajectory. The dynamic smearing model is then obtained, also in an analytical form. After that, three sets of typical simulating maps and data are simulated from this dynamic model manifesting the expected smearing effects, also compatible with the linear model as its special case of no boresight rotation. Finally, model validity tests on a rate turntable are carried out, which results in a mean correlation coefficient 0.920 0 between the camera images and the corresponding model simulated ones with the same parameters. The sufficient similarity verifies the validity of the dynamic smearing model. This model, after parameter calibration, can serve as a front-end loop of the ground semi-physical simulation system for celestial attitude determination with strapdown star sensor.     

Asymptotic Performance of Sparse Signal Detection Using Convex Programming Method

The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to ease detection. In this paper, we consider the general unknown and arbitrary sparse signal detection problem when no prior knowledge is available. Under a Neyman-Pearson hypothesis-testing framework, a new detection scheme is proposed by combining a generalized likelihood ratio test (GLRT)-like test statistic and convex programming methods which directly exploit sparsity in an underdetermined system of linear equations. We characterize large sample behavior of the proposed method by analyzing its asymptotic performance. Specifically, we give the condition for the Chernoff-consistent detection which shows that the proposed method is very sensitive to the 2 norm energy of the sparse signals. Both the false alarm rate and the miss rate tend to zero at vanishing signal-to-noise ratio (SNR), as long as the signal energy grows at least logarithmically with the problem dimension. Next we give a large deviation analysis to characterize the error exponent for the Neyman-Pearson detection. We derive the oracle error exponent assuming signal knowledge. Then we explicitly derive the error exponent of the proposed scheme and compare it with the oracle exponent. We complement our study with numerical experiments, showing that the proposed method performs in the vicinity of the likelihood ratio test (LRT) method in the finite sample scenario and the error probability degrades exponentially with the number of observations.     

Defect Recognition in Thermosonic Imaging

This work is aimed at developing an effective method for defect recognition in thermosonic imaging.The heat mechanism of thermosonic imaging is introduced,and the problem for defect recognition is discussed.For this purpose,defect existing in the inner wall of a metal pipeline specimen and defects embedded in a carbon fiber reinforced plastic(CFRP) laminate are tested.The experimental data are processed by pulse phase thermography(PPT) method to show the phase images at different frequencies,and the characteristic of phase angle vs frequency curve of thermal anomalies and sound area is analyzed.A binary image,which is based on the characteristic value of defects,is obtained by a new recognition algorithm to show the defects.Results demonstrate good defect recognition performance for thermosonic imaging,and the reliability of this technique can be improved by the method.     

新型航空航天飞行器概念研究的方法

 本文概述了新型航空航天飞行器概念研究的目的、内容和方法。并介绍了适用于概念研究的系统分析程序,其中着重介绍程序接口和分析程序的发展情况,此外还对新型航空航天飞行器概念研究的主要结果作了简要的评述。     

发动机故障诊断的主特征量模型

本文提出了发动机状态监控气路分析的主特征量模型。其基本原理如下:对于发动机部件匹配热力学关系式的小偏差方程组,利用最优化方法求出各种可能的故障组合的最优解,并根据合理性判据选择合理的最优解。它可以在可能的故障参数数目大于测量参数数目的情况下,对主要故障参数进行故障诊断。与目前广泛采用的影响系数矩阵法比较,主特征量模型可以用于测量参数数目较少的情况,并且可以给出较多的故障诊断信息,因此具有广泛的实用意义。文中给出了主特征量模型的三种数学模型,讨论了利用主特征量模型进行故障诊断的有关技术问题,并且通过计算机模拟方法对主特征量模型的适用性及可靠性进行了分析。研究结果表明,本文提出的主特征量模型是发动机状态监控与故障诊断的一种有效方法。     

模式电压和模式电流在分析谐振腔中的应用

本文由理想的金属波导管中模式电压和模式电流的沿线分布表达式导出了对于终端短路的波导,模式电压和模式电流沿线分布表达式,并利用该表达式求解出谐振腔中场分量表达式。     

C／SiC复合材料与Nb的液相渗透连接

研究了不同编织方法的C/SiC复合材料与金属Nb的连接情况。采用液相渗透连接方法以Ni基连接剂为中间层在1300℃、保温时间45min、压力20MPa、真空条件下分别对二维、三维C/SiC复合材料与金属Nb进行了连接。结果表明二维C/SiC复合材料与金属Nb不能得到较好的连接,整个连接件在由连接温度降温到室温过程中已发生脱离现象;而三维C/SiC复合材料与Nb金属连接良好。     

C／SiC复合材料与CVDSiC涂层的结合性能研究

采用先驱体转化法(PIP方法)制备C/SiC陶瓷基复合材料,通过调整多孔预制件的体积密度制备出不同组分比的C/SiC复合材料。结果显示,C/SiC复合材料的热膨胀系数随着复合材料中SiC含量的增加而增加,其与CVDSiC涂层之间的热匹配也相应增加,通过CVI方法制备梯度过渡层,在C/SiC复合材料表面制备出致密度较高的CVDSiC涂层。