Mechanical wear debris feature,detection, and diagnosis: A review

Mechanical debris is an important product of friction wear, which is also a crucial approach to know the running status of a machine. Many studies have been conducted on mechanical debris in related fields such as tribology, instrument, and diagnosis. This paper presents a comprehensive review of these studies, which summarizes wear mechanisms (e.g., abrasive wear, fatigue wear, and adhesive wear) and debris features (e.g., concentration (number), size, morphology, and composition), analyzes detection methods principles (e.g., offline: spectrograph and ferrograph, and online: optical method, inductive method, resistive-capacitive method, and acoustic method), reviews developments of online inductive methods, and investigates the progress of debris-based diagnosis. Finally, several notable problems are discussed for further studies.     

辐射源细微特征用于个体识别的可行性分析

首先分析了辐射源细微特征应该具有的基本特性,并给出了辐射源的(潜在)细微特征参量、测量准确度的影响因素及应用限制条件.然后,给出了辐射源细微特征差异、参数测量精度与正确分辨概率之间的定量关系,为判断细微特征差异能否用于个体识别提供了理论依据.最后,作了举例说明.     

基于二分法的EKF SLAM算法

针对基于点特征的SLAM算法对实际环境描述运算量大的缺陷,提出了基于二分法的线特征SLAM仿真算法。通过判断机器人点到线特征直线的垂足所在位置选择不同的计算顺序,避免了直接求解带来的较大运算量。算法分析表明,该SLAM算法可以减少运算量,提高计算速度,并增强机器人的构图定位能力。基于该算法进行了仿真实验,实验结果表明,该算法有效地提高了运算速度,使得机器人可以更好地完成构图定位任务。     

直射式喷嘴跨流喷射的雾化特性试验研究

 应用Malvern激光测雾仪在气流速度50～150m/s,供油压力（1.1～4.2）×10⁶Pa,喷嘴直径0.5～0.9mm,喷嘴下游距离60～250mm参数范围内对直射式喷嘴跨流喷射的雾化特性进行了研究。根据试验结果得出了相应的经验关系。     

基于特征的航空机载设备壳体类零件CAD系统

为了满足航空机载设备壳体类零件集成制造的需求，建立了基于特征和STEP标准的零件集成信息模型，以此为基础在UG II 平台上利用UG/Open API接口开发了一个基于特征的CAD系统。该系统为制造后续环节提供较完备的零件设计和制造信息，便于实现零件设计、制造、测量的集成。     

武装直升机空战关键技术问题研究

本文论述了武装直升机空战的几个关键技术问题。首先建立了简化的武装直升机空战动力学和运动学模型,阐明了模型简化的具体方法;其次给出了直升机空战的结构图,并分析了空战的基本原理,同时简述了空战机动策略的选取原则,描述了直升机空战的基本特征;最后系统地说明了直升机空战中的航路规划技术,并提出了未来旋翼机的设想。     

一种基于亚像素匹配的高精度视觉定位方法

大多数应用到无人机景象匹配导航中的匹配算法都只能满足像素级精度,且当无人机利用景象匹配定位时图像之间往往存在较大的视觉差异,这种情况下图像匹配精度低且性能会急剧下降。所以选用具有仿射不变特性的特征点进行匹配,结合高斯亚像素拟合原理及特征描述符简化方法,并采用渐进采样一致性(PROSAC)算法剔除误匹配点,最终实现亚像素级的景象匹配定位。实验结果表明,采用此方法可以大大提高图像匹配的精度,提高到0.05像素以内。     

基于图像奇异值描述的雷达目标识别方法

利用目标对常规雷达发射波形的调制效应，先对录取的回波数据进行预处理，把一维回波序列投影成二维灰度图像，然后提取这种图像的反映飞机目标不同机型(大、小)和不同架次的奇异值作为特征矢量，采用BP神经网络对目标进行分类识别试验，结果表明该方法是有效的，这为常规低分辨雷达空中目标识别提供了一种新方法。     

基于人工神经网络的多模型目标跟踪算法

针对在目标跟踪中单模型跟踪算法难以应对目标运动形式的变化,而多模型跟踪算法存在结构固定、跟踪精度被非匹配模型削弱且模型切换缓慢的矛盾,文章提出了一种基于人工神经网络的多模型目标跟踪算法。通过分析目标几种基本运动模式的轨迹特点,归纳出目标运动轨迹的特征向量。利用训练好的BP神经网络对滑窗里的轨迹段进行运动模型识别,按结果进行跟踪模型切换,达到使跟踪算法实时适应目标运动状态的目的。仿真结果证明了该算法的有效性,且与传统的多模型算法相比,具有结构更加简单、更强的灵活性和拓展性的特点。     

Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.