发动机叶片榫头角度现场检测方法

对航空发动机叶片榫头角度进行现场测量是保证叶片加工质量的重要环节。本文结合叶片榫头的结构特点,针对使用传统的专用测具和标准件测量榫头角度存在的问题,设计了一种叶片榫头角度检测仪,并给出了相应的检测方法。实验和使用证实,该检测仪能提高检测效率,降低劳动强度,适合在生产现场使用。     

Scalable Preparation of SrTiO3 Submicro-wires from Layered Titanate Nanowires

SrTiO3 submicro-wires were prepared by the reaction of layered titanate nanowires with Sr(OH)2 powder in an autoclave. The wires were investigated using X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), Ultra-violet visible (UV-vis), photoluminescence (PL) and Raman spectroscopy. The XRD measurement shows that the prepared SrTiO3 submicro-wires hardly have impurity phases. The SEM and TEM images demonstrate that the scalable wires, which need to be proc- essed at the reaction temperature of 180 ℃ for about 48 hours, are not composed of single crystals. The PL shows that the wire-like SrTiO3 has emission peaks at the wavelengths of 568 and 585 nm. Further, the Raman spectroscopy reveals structural changes in the products through different reaction time.     

Multi-block SSD based on small object detection for UAV railway scene surveillance

A method of multi-block Single Shot MultiBox Detector (SSD) based on small object detection is proposed to the railway scene of unmanned aerial vehicle surveillance. To address the limitation of small object detection, a multi-block SSD mechanism, which consists of three steps, is designed. First, the original input images are segmented into several overlapped patches. Second, each patch is separately fed into an SSD to detect the objects. Third, the patches are merged together through two stages. In the first stage, the truncated object of the sub-layer detection result is spliced. In the second stage, a sub-layer suppression and filtering algorithm applying the concept of non-maximum suppression is utilized to remove the overlapped boxes of sub-layers. The boxes that are not detected in the main-layer are retained. In addition, no sufficient labeled training samples of railway circumstance are available, thereby hindering the deployment of SSD. A two-stage training strategy leveraging to transfer learning is adopted to solve this issue. The deep learning model is preliminarily trained using labeled data of numerous auxiliaries, and then it is refined using only a few samples of railway scene. A railway spot in China, which is easily damaged by landslides, is investigated as a case study. Experimental results show that the proposed multi-block SSD method produces an overall accuracy of 96.6% and obtains an improvement of up to 9.2% compared with the traditional SSD.     

卫星与深空动态场景实时仿真系统

卫星与深空动态场景的实时仿真对于航空航天、军事国防等领域有着重要意义。现提出了一个深空动态场景的绘制方法，该方法综合了计算机图形学和天文学的知识，建立了基于天文学星表的深空场景模型，计算出卫星及各星体的运行轨迹，实现了卫星目标和深空场景的真实感合成，并采用一系列加速绘制技术，最终实现了深宅动态场景的实时生成和交互式虚拟漫游。     

影响惯性仪表精度长期稳定的材料学问题与对策

陀螺仪和加速度计等惯性仪表的精度对零组件的尺寸变化有着极其敏感的反应。随着对惯性仪表精度及其稳定性研究的深入,发现材料的尺寸不稳定是导致精度稳定性差的主要原因之一。以多种惯性仪表构件的常用材料为例,从材料学角度系统综述了微观缺陷、第二相、晶粒和织构、内应力以及环境因素对材料尺寸稳定性的影响规律,并提出了如何从材料内禀特性出发改善惯性仪表精度长期稳定性,展望了惯性仪表材料与工艺的未来发展方向。     

Lyapunov自适应滤波及其 在INS/SMNS组合中的应用

为克服在惯导/景像匹配导航系统(INS/SMNS,Inertial Navigation System/Scene Matching Navigation System)组合导航系统中随着匹配点增多最小二乘法易出现发散的缺点,提出了一种基于多输入多输出(MIMO,Multi-Input-Multi-Output)系统的改进型Lyapunov自适应滤波算法.该方法利用观测方程信息,通过定义滤波误差和预测误差获得算法的递推公式,而算法的稳定性和收敛性可由Lyapunov稳定性理论来证明.以INS/SMNS组合导航系统为例进行了仿真验证,和递推最小二乘算法相比该算法简单、可靠,而且滤波的性能优于递推最小二乘算法.     

密度变化与韧性损伤的关系

通过精密测量相对密度化建立韧性损伤模型,以预测金属塑性加工过程中韧性损伤演化规律和产品质量。本文研究了精密测量微小密度的变化、介绍了测量方法和装置。通过测量相对密度变化对拉伸和扭转过程中韧性损伤演化规律进行了研究。     

基于Vega的无人直升机飞行视景监测系统开发

针对某型无人直升机超视距飞行需求,提出基于Vega软件平台开发一套无人直升机视景监测系统,给出了系统的设计方案及构建流程,论述了视景模型建立、Vega场景模型配置以及Vega实时驱动等关键技术的实现,并完成了系统的开发。飞行试验表明系统满足无人直升机超视距飞行监测所需的实时性及真实感要求,有效地提高了地面监测效率。     

基于组合跟踪的景象匹配分析评估方法

景象匹配飞行试验中,图像序列中存在的剧烈尺度变化及多种外界因素影响导致的几何变形等成像质量变化,增加了景象匹配全流程自动评估的难度.为了解决这个问题,提出1种基于组合跟踪的景象匹配图像全流程评估方法.首先,基于序列图关键帧选取原则,提出序列图关键帧匹配方法;然后将该方法与多种目标跟踪算法进行对比分析;再根据对比分析的结...     

土壤有机碳对土地利用方式变化的响应

以重庆市北碚区5种土地利用方式为研究对象,研究了土壤剖面有机碳和有机碳密度对土地利用方式变化的响应.结果表明：（1）土壤有机碳平均含量的多少顺序表现为水田变菜地,旱地变菜地,水田变果园,水田变旱地,旱地变果园;（2）水田变旱地、旱地变为果园后有机碳含量呈降低趋势,而旱地变为菜地后有机碳含量呈增加的趋势;（3）表层（020cm）土壤有机碳密度大小顺序表现为旱地变菜地,水田变菜地,水田变果园,旱地变果园,水田变旱地;而2060cm厚度土壤有机碳密度表现为变化前为水田的土壤有机碳密度大于变化前为旱地的土壤有机碳密度.