基于划分检测模型的终端区异常轨迹检测方法

针对异常轨迹对轨迹聚类效果的影响以及给进离场程序管制适用性的量化分析提供分析数据的考虑，在结合数据挖掘中异常检测理论的基础上，利用划分检测框架及将距离和密度结合起来，设计了一种有效检测算法，运用到终端区飞行轨迹的异常检测当中，检测出飞行轨迹中的异常轨迹，从而改善轨迹的聚类效果。实例仿真结果表明：方法可以准确地检测出异常轨迹。     

波音737系列飞机过热探测系统原理分析及排故技巧

轮舱火警、机翼及后下部机身的过热探测系统是飞机防火系统的重要组成部分，且故障发生频繁。本文介绍了波音737系列飞机的轮舱火警、机翼及后下部机身的过热探测系统的基本原理及常见故障，并结合外场维修经验介绍了排除该系统故障的一些技巧。     

基于ANSYS的同面多电极电容传感器仿真研究

同面多电极电容传感器是一种新的飞机复合材料构件损伤检测技术,该检测技术的正问题中敏感场分布函数的计算要涉及到静电场中电容计算问题。在仿真研究中,电容要通过场的数值计算方法来求得。本文介绍了如何使用ANSYS有限元分析计算同面多电极电容传感器中的各电极对之间的电容,对检测材料发生异常及传感器参数改变时电容的变化进行了分析,为损伤检测的特征提取和逆问题图像重构提供了仿真数据。     

某火箭发动机故障检测及诊断算法设计分析

针对某型号液体火箭发动机故障检测及诊断软件存在瞬态段（起动段、关机段）故障检测功能缺失、故障诊断无法给出故障量大小的问题，在原软件故障诊断算法——余弦相似度分类的基础上，通过引入故障因子定量给出故障量大小，实现发动机故障诊断的定性定量分析。同时，采用基于统计学基础的包络线算法，通过Python语言对发动机瞬态段故障检测算法进行设计开发，使原软件实现发动机瞬态段故障检测功能。通过仿真试车数据对软件算法进行验证，结果表明优化后的故障诊断功能可实现故障量大小计算，基于包络线算法开发的故障检测功能提高了发动机故障检测效率。     

Hypothesis-test-based landcover change detection using multi-temporal satellite images – A comparative study

Remote sensing images and technologies have been widely applied to environmental monitoring, in particular landuse/landcover classification and change detection. However, the uncertainties involved in such applications have not been fully addressed. In this paper two hypothesis-test-based change detection methods, namely the bivariate joint distribution method and the conditional distribution method, are proposed to tackle the uncertainties in change detection by making decisions based on the desired level of significance. Both methods require a data set of class-dependent no-change pixels to form the basis for class-dependent hypothesis test. Using an exemplar study area in central Taiwan, performance of the proposed methods are shown to be significantly superior to two other commonly applied methods (the post-classification comparison and the image differencing methods) in terms of the overall change detection accuracies. The conditional distribution method takes into consideration the correlation between digital numbers of the pre- and post-images and the effect of the known pre-image digital number on the range of the post-image digital number, and therefore yields the highest change detection accuracy. It is also demonstrated that the class-dependent change detection is crucial for accurate landuse/landcover change detection.     

TEST OF BOARD-LEVEL BOUNDARY SCAN INTEGRITY

ＩＥＥＥ１１４９．１边界扫描为数字电路板级测试提供了所需的对内部节点的控制和观察能力。但是，边界扫描测试结构本身的完整性必须首先加以检测，以保证其他功能测试和诊断结果的正确性。本文论述了板级边界扫描测试存取口的故障模型和测试原理，并针对全边界扫描印制板提出了一种故障覆盖率高、测试时间短的测试算法。     

基于光纤F-P可调谐滤波器的有害气体检测方法

光谱分析法在气体成分监测领域有着广泛的应用,实现小型紧凑高分辨率的光谱测量装置是热门的研究课题。文章创造性的提出了基于光纤法布里-帕罗（F—P）的可调谐滤波器提高吸收光谱分辨率,为构建紧凑高分辨率的光谱仪提供了一种新的方案。基于光纤F-P的可调谐滤波器成功实现了微型光栅光谱仪（分辨率约1nm）对甲烷吸收光谱的测量,对比无光纤F—P可调谐滤波器直接测量的结果,该方法测得的吸收光谱强度至少提高了一个数量级。此研究成果可用于紧凑高分辨率的星载气体检测仪的研制。     

一种遥感图像建筑物检测新方法

遥感图像中的建筑物检测对于土地规划和地图绘制等具有重要意义。文章针对高分辨率全色遥感图像植被覆盖中隐蔽建筑物检测问题,提出了一种结合屋顶结构信息和纹理信息的快速房屋检测方法。首先利用屋顶边缘的几何关系寻找具有矩形屋顶的建筑物;然后使用形态学方法提取屋顶较亮的建筑物;最后利用局部二值模式（Local Binary Pattern,LBP）描述屋顶的纹理特征,并利用支持向量机（Support Vector Machine,SVM）排除误检区域。通过在全色遥感图像集上的试验证明,所提方法对高分辨率遥感图像植被覆盖区域中的建筑物目标具有较高检测率和较低误检率。     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

基于模块度的复杂网络社团结构聚类新算法

针对传统的分裂聚类算法删除连边会影响节点划分的问题,结合K-means算法的思想并加以改进,提出了一种以邻居节点为聚类备选集,所有社团中心节点同时聚类的同步聚类算法。该算法根据节点中心度和最短路变化率确定社团中心节点集,然后以中心节点为社团中心,以邻居节点为聚类备选集合进行聚类,完成社团的划分。将算法应用到Zachary网络中并与GN算法、Top Leader算法进行比较,仿真结果表明该算法对网络有较好的划分。