短波SFH／CPM系统差分相位检测方案的性能分析

文章提出了一种基于Viterbi算法的短波SFH／CPM系统差分相位检测（DPD）的解调方案,运用Matlab建立了短波SFH／CPM系统模型,并在此模型上对该解调方案的误比特率进行了数值仿真。其仿真结果表明：DPD解调方案的误比特率可以达到10^-5～10^-6,能满足短波信道性能的需求。     

基于自适应分段混合系统的轴承故障诊断

针对强噪声背景下轴承早期故障的诊断问题,提出一种基于自适应分段混合随机共振（adaptive piecewise hybrid stochastic resonance,APHSR）系统的检测方法。采用经验模态分解法（EMD）进行信号预处理,分别采用能量密度法和相关系数法去除高、低频噪声,自动筛选最优固有模态函数,经尺度变换后输入分段混合随机共振系统模型,提取故障信号。工程实验显示:经过APHSR系统,轴承故障特征频率的频谱幅值、频谱幅值与周围最大噪声之差和最大信噪比（SNR）均高于经验模态分解和经典随机共振方法,其中齿轮箱故障轴承信噪比分别提高了9.579 dB和7.473 dB,转子故障轴承信噪比分别提升了8.597 dB和5.695 dB,对凯斯西储大学故障轴承数据处理后的信噪比分别提升了3.369 dB和17.043 dB。数据表明APHSR方法具有高效性,提高了轴承故障信号诊断能力。      

基于机器视觉与UMAC的自动铺丝成型构件缺陷检测闭环控制系统

为保证自动铺丝成型构件的性能,实现对成型构件表面质量的高效检测,本文基于机器视觉检测技术,自行研发自动铺丝成型构件表面缺陷检测闭环控制系统,使自动铺丝过程中预浸纱之间的间隙或重叠在允许范围内,从而保证铺丝精度。研究主要分为三个部分:铺丝成型构件表面图像提取与缺陷检测,检测数据传输,运动轴反馈控制,实现在自动铺丝过程中对成型构件表面缺陷检测实时闭环控制。针对电荷耦合相机采集到的预浸纱图像存在运动模糊和信噪比低等问题,将图像预处理划分为图像复原和降噪两大功能,根据不同类型的噪声采用对应滤波法进行降噪处理,提高了图像的信噪比,为后续检测提供高质量图像;预浸纱缺陷主要由其边缘直线这一几何特征进行表征,因此通过对预浸纱边缘检测实现缺陷识别;利用工控机向图像采集控制器发送命令实现图像采集,同时通过工控机与运动控制器之间信息流和数据流的交换实现检测数据的传输。探讨模糊控制理论用于闭环控制的研究,在反模糊化环节后面,加入自适应参数调节,以适应加工过程的突变,并成功地应用到自动铺丝缺陷检测闭环控制系统中,提高了伺服跟踪精度和跟踪实时性,从而提高铺丝精度。     

An intelligent target detection method of UAV swarms based on improved KM algorithm

Complete and efficient detection of unknown targets is the most popular application of UAV swarms. Under most situations, targets have directional characteristics so that they can only be successfully detected within specific angles. In such cases, how to coordinate UAVs and allocate optimal paths for them to efficiently detect all the targets is the primary issue to be solved. In this paper, an intelligent target detection method is proposed for UAV swarms to achieve real-time detection requirements. First, a target-feature-information-based disintegration method is built up to divide the search space into a set of cubes. Theoretically, when the cubes are traversed, all the targets can be detected. Then, a Kuhn-Munkres (KM)-algorithm-based path planning method is proposed for UAVs to traverse the cubes. Finally, to further improve search efficiency, a 3D real-time probability map is established over the search space which estimates the possibility of detecting new targets at each point. This map is adopted to modify the weights in KM algorithm, thereby optimizing the UAVs’ paths during the search process. Simulation results show that with the proposed method, all targets, with detection angle limitations, can be found by UAVs. Moreover, by implementing the 3D probability map, the search efficiency is improved by 23.4%–78.1%.     

Multi-coset angular sampling-based compressed sensing of blade tip-timing vibration signals under variable speeds

Blade Tip-Timing (BTT) has been regarded as a promising way of on-line blade vibration monitoring. But blind multi-band BTT vibration reconstruction is a big challenge under variable speeds and under-sampling. In order to deal with it, a novel Compressed Sensing (CS) method is proposed based on Multi-Coset Angular Sampling (MCAS) in this paper. First, multi-coset sampling scheme of BTT vibration signals is presented. Then the CS model of BTT vibration signals is derived in order domain. A sufficient condition of the number of BTT sensors is derived for perfect reconstruction and optimal placement of BTT sensors is determined by minimizing the condition number. In the end, numerical simulations are done to validate the proposed method and the performances of four reconstruction algorithms are compared, i.e., Orthogonal Matching Pursuit (OMP), Multiple Signal Classification (MUSIC), Basis Pursuit Denoising (BPDN) and Modified Focal Underdetermined System Solver (MFOCUSS). Influences of the sensor placement, the number of BTT sensors and measurement noises on the reconstruction performances are also testified. The results demonstrate that the proposed method is feasible and the overall performance of the BPDN algorithm is the best among the four algorithms. Also the reconstruction performance decreases with the accelerations of rotating speed.     

基于光学图像的撞击坑识别研究综述

当前,随着深空探测研究工作的需要,将信息科学的图像处理、模式识别技术应用到空间探测领域成为必然。基于光学图像的撞击坑自主检测技术就是将信息科学的图像处理技术应用到空间科学研究中的一个很好例证,近年来得到了各国学者的重视。本文针对这一领域的相关研究进行了介绍与分析。首先,对这一技术的研究意义从地质学、天体表面结构和特征数据库建设、探测器导航三个角度加以说明;其次,详细阐述了该技术的研究现状,简要介绍了其中一些经典算法,并将相关算法分为三类:全自主检测算法、半自主检测算法和组合检测算法;最后,提出了该技术研究所面临的难点和未来研究方向与应用空间,以及介绍了作者在这一方面的研究进展。     

基于支持向量机的Webshell黑盒检测

Webshell是一种基于Web的网站后门程序。当前已有的Webshell检测方法都需要根据脚本程序源代码来检测,因此只能部署在服务器主机上,而且只能检测本机的网站代码。本文通过分析Webshell的HTML页面特征,提出了一种基于支持向量机(Support vector machine,SVM)分类算法的黑盒检测方法。该方法是一种有监督的机器学习系统,对先验网页的HTML页面进行学习,可以在未知脚本源代码的情况下对Webshell进行检测。实现结果表明,该方法在黑盒的条件下达到了较高的准确率和极低的误报率,并且取得了与白盒检测方法相近的检出率,可以部署在基于网络的入侵检测系统中,同时监测多台服务器是否包含Webshell,从而帮助监控入侵趋势和网络安全态势。     

遥感器真空成像三维光学检测装置的设计与应用

在以往的遥感器真空成像试验中, 光学检测装置每次装配完毕只能完成单一状态下的光学测试, 且建立成像试验所需工况的周期较长。文章设计研制了一种三维光学检测装置, 使用该装置可实现中小口径相机在空间环境模拟装置内的光电综合性能检测。试验人员可在空间环境模拟容器外对该装置进行平移、旋转和俯仰的精确调整, 完成对单台或多台相机全视场的精确测试。试验验证了该装置方案设计的可行性。     

动态情况下星敏感器探测灵敏度研究

针对同样曝光时间下星敏感器动态探测灵敏度较静态低的事实,根据像元输出模型和从噪声中检测信号的理论,提出含有有效信号的像元能否被探测到的信噪差比判据．论证了把w-1m像元可探测性作为星像轨迹被提取的奈件的合理性,基于此研究了动态探测灵敏度的计算方法,并对一实际星敏感器动态探测灵敏度进行各种参数条件下的计算、比较和分析．     

用一种改进的蚁群聚类算法进行网络入侵检测

针对蚁群聚类算法在聚类结果中出现部分数据划分不够准确的问题,提出蚁群聚类改进算法。对已有蚁群聚类算法的结果簇做调整,从而得到更好的聚类结果。使用KDD Cup1999入侵检测数据集所作的实验结果表明,聚类效果改进明显,入侵检测率有所提高。