Molecular Hydrogen

Observations of H₂ line emission in galactic and extragalactic environments obtained with the Infrared Space Observatory (ISO) are reviewed. The diagnostic capability of H₂ observations is illustrated. We discuss what one has learned about such diverse astrophysical sources as photon-dominated regions, shocks, young stellar objects, planetary nebulae and starburst galaxies from ISO observations of H₂ emission. In this context, we emphasise use of measured H₂ line intensities to infer important physical quantities such as the gas temperature, gas density and radiation field and we discuss the different possible excitation mechanisms of H₂. We also briefly consider future prospects for observation of H₂ from space and from the ground. Based on observations with ISO, an ESA project with instruments funded by ESA Member States (especially the PI countries: France, Germany, The Netherlands, and the United Kingdom), and with the participation of ISAS and NASA.     

基于Fuzzy数学的飞机自动停车故障诊断

飞机本身是一个复杂的系统.因此,系统及分系统的故障也是纷繁复杂的,反映在故障征兆(表象)与原因上,同一故障征兆可能是多种原因所引起的,而同一故障原因又往往产生多种故障征兆.对于故障征兆与故障原因间的复杂隶属关系,如果使用传统的经典数学模型来处理往往不能准确的解决问题.本文将模糊数学方法引入到飞机故障诊断中,建立了某型飞机自动停车故障诊断的数学模型,解决了针对一种或数种故障征兆,如何准确、快速地找到引起故障的真正原因,并且针对最大隶属度原则的缺陷,改进了该原则,此诊断方法可以按飞机系统功能分解推广到对任一分系统(如液压系统,燃料系统,冷气系统,着陆装置系统等)的故障诊断.     

Research on the Algorithm of Avionic Device Fault Diagnosis Based on Fuzzy Expert System

Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic element is the test-diagnosis fault unit. Every underlying fault cause’s membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples, the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.     

Deuterium Fractionation in Interstellar Clouds

This paper reviews the chemical processes responsible for fractionating deuterium in interstellar molecules. I show that this process is intrinsically a low temperature phenomenon and discuss how the degree of enhancement of the deuterium content of molecules is related to the physical conditions, particularly abundances, in molecular clouds. If significant amounts of abundant species, such as CO, are frozen out on to interstellar dust grains, the resulting enhancement in H₂D⁺ can result in its abundance being greater than that of H ₃ ⁺ at 10K. Transfer of the deuteron from H₂D⁺ can then lead to the efficient formation of multiply deuterated species, such as NHD₂ and ND₃. Fractionation can also occur in grain surface reactions and some simple models are discussed. This revised version was published online in August 2006 with corrections to the Cover Date.     

基于模糊理论的复合材料超声检测缺陷类型识别

本文以复合材料常见缺陷分层、孔隙、疏松的超声波检测缺陷信号为研究对象,选取缺陷波的时域及频域特征,考虑到各特征量之间的不可避免地存在耦合关系,而且对缺陷区分的重要性、敏感度也有很大的差别,采用加权多面体隶属度概念构造隶属函数,依据最大隶属原则进行模式识别,从而区分复合材料缺陷类型。     

非线性椭球集员滤波及其在故障诊断中的应用

 针对带有未知但有界噪声的非线性系统，提出一种椭球集员滤波算法，并将其应用于保证故障检测与隔离。对非线性状态方程和量测方程进行泰勒展开之后，通过区间分析的方法给出线性化余项存在区域的盒子外界描述。假设过程和量测噪声由盒子限界，在算法的时间更新和量测更新过程中，分别计算包含椭球与线段的向量和及椭球与带的交的次最小容积椭球。在椭球集员滤波算法的基础之上，给出传感器故障检测与隔离的方法。由于集员滤波是保证状态估计，因而基于集员滤波算法的故障检测与隔离方法也具有保证性，即如果发出故障警报，则一定有故障发生。一个二维非线性系统的例子说明了该方法的有效性。     

集员辨识与T-S模型相结合的非线性系统建模及其故障检测算法

针对带有未知但有界（Unknown But Bounded．UBB）噪声的非线性系统的建模及其故障检测问题，提出了一种集员辨识与T-s模糊模型相结合的非线性系统建模及其故障检测算法。在建立非线性系统模型时，利用系统正常状态下的运行数据，选用T-S模型对其进行离线建模。首先采用模糊聚类的方法对输入空间进行模糊划分，然后利用T-S模型为参数线性模型的特点，使用参数线性集员辨识算法辨识T-S模型的结论参数。由于集员辨识算法所得到的是参数的集合估计，在系统运行过程中，可以很方便地利用所建模型预测实际系统的输出范围，如果测量所得实际系统的输出不在预测输出范围之内，则可判断系统发生了故障。通过与其他算法相比，验证了本方法的性能。     

考虑非高斯相关噪声的视线角速率提取算法

针对捷联导引头敏感信息存在非高斯噪声且状态噪声与观测噪声相关的问题,提出了修正球面坐标系下带有相关噪声解耦的扩展椭球集员滤波（ESMF）算法。首先,通过对弹目相对距离及其变化率的规范化处理,得到修正球面坐标系下的视线角速率提取模型;然后,利用相关噪声解耦方法去除观测方程中耦合的状态噪声项,基于泰勒级数展开推导了相关噪声解耦后的模型线性化表达式,得到包含线性化误差的虚拟噪声椭球集合,并根据最小迹和最小化尺度因子上界的优化方法得到状态更新与观测更新椭球,形成非高斯相关噪声解耦的扩展椭球集员滤波算法。仿真结果表明,所提算法能够在考虑非高斯相关噪声的情况下,实现捷联导引头视线角速率的高精度提取。     

一种基于模糊熵的自适应多层模糊增强算法

针对传统多级模糊增强算法中边缘附近灰度值的选取缺乏理论依据,增强变换可能导致灰度集中的现象,提出一种基于模糊熵的自适应多层次增强算法,该方法通过图像模糊熵估计边缘附近灰度,定义新的隶属度函数和增强算子,实现了图像的自适应增强.     

基于经验模态分解的点云数据平滑与增强

在计算机辅助设计与逆向工程应用中,针对缺乏拓扑连接关系的点云数据,提出了基于经验模态分解(EMD)的点云数据平滑与增强算法。首先,以点云模型的拉普拉斯矩阵坐标与法向的内积作为EMD输入信号,提取点云模型输入信号的极值点作为插值节点计算信号的上下包络;然后,为实现特征保持的EMD信号分解,通过检测点云数据上特征点,并在计算信号上下包络的过程中作为约束,克服传统EMD算法无法保持特征的局限;最后,迭代地从输入信号中减去上下包络的均值得到内蕴模态函数(IMF)和余量,并通过设计滤波器实现了点云数据平滑和增强。实验结果表明,本文算法有效地将EMD推广到三维散乱点云数据中,扩大EMD在三维几何中的应用范围,并在点云数据平滑和增强方面取得了很好的效果。