基于边缘计算和VPRS的火箭设备单机双层判读与实时诊断

为提高参数自动判读的效率，增强设备单机状态诊断的时效性和准确性，提出一种基于边缘计算和变精度粗糙集(VPRS)的运载火箭设备单机双层判读与实时诊断方法。首先构建了边缘层-判读服务器层的双层判读架构。然后，基于边缘计算技术设计了边缘层判读方法，对参数原始数据进行阈值判断与数据筛选。随后，在判读服务器层，定义AIPL(AutoIP Language)判据描述语言设计高阶判据并进行高阶判读；基于VPRS建立了实时诊断模型，对设备单机的历史数据进行约简，挖掘出了简化后的状态诊断规则。最后，以XX火箭设备单机遥测数据自动判读系统升级改造为例，验证了所提方法的可行性与有效性。     

Automatic lineament extraction in a heavily vegetated region using Landsat Enhanced Thematic Mapper (ETM+) imagery

Lineament extraction from satellite remotely sensed data has been one of the widely used applications of remote sensing in geology. In fact, recent advances in digital image processing allow such lineament extraction to be accomplished in semi-automatic to fully automatic approaches. However, satellite remotely sensed data acquired in heavily vegetated regions such as tropical rainforest, are vulnerable to higher inherent noise levels attributed to the resultant effects of scattering by clouds and adjacency effects of highly inhomogeneous vegetation cover within the pixel dimension. In this study, we examined the effects of noise levels to lineament extraction using a fully automatic approach, consisting of a combination of edge-line detection algorithms. Ancillary information from a digitized topographic map and image classification was used to discriminate between cultural and natural lineaments from the extracted lineaments. Adapting the combination of edge detection and a line-linking algorithm, we have found the optimal parameters for automatic lineament extraction of such complex areas using Enhanced Thematic Mapper (ETM+) data. A noise level of 30% is the maximum threshold before artifacts are generated. It is therefore concluded that the combination of edge-based and line-linking digital image processing operations with the priori local optimal parameters is crucial in lineament feature extraction in heavily vegetated regions.     

Improvements in bottomside electron density definition in the Autoscala program

Some improvements introduced in the Autoscala program are presented. They include improvements in E valley modeling of the electron density profile N_e(h), and in the link between the E valley and bottom-side F regions. An abrupt variation in N_e(h) generated by the previous version of Autoscala under night conditions has been eliminated.A series of ionograms recorded by the Millstone Hill digisonde (42.6°, 288.5°) were automatically interpreted by the previous version of Autoscala and by the new one. Data from Incoherent Scatter Radar (ISR) were used to comparatively assess the performance of the two versions. For this purpose, the root mean square errors (RMSEs) of the N_e(h) provided by Autoscala were calculated relative to the corresponding values provided by ISR.A more accurate overall modeling of N_e(h) was achieved by the new Autoscala version (RMSE = 0.51 MHz for the new version against RMSE = 0.67 MHz for the previous one).     

自动钻铆技术在直升机机身总装中的应用研究

针对直升机装配行业的高质量、高效率的自动化装配需求,提出一种直升机机身总装自动钻铆系统。对直升机机身总装自动钻铆系统的功能、结构及关键技术进行了详细说明,此项研究系统可有效缩短直升机的研制周期、降低成本和提高竞争能力。     

多介质气体微小流量标准装置设计探讨CSCD

介绍了气体流量计量发展的特点及需求,提出建立一套多介质气体微小流量标准装置。结合实际装置指标需求,比较分析了常用气体流量标准原理特点,确定采用了PVTt法原理,根据设计指标需求及原理提出了多介质气体微小流量装置整体初步设计方案,并进行了测量不确定度分析。     

TDS600系列数字示波器自动验收系统

ＴＤＳ６００系列数字示波器自动验收系统，采用人机对话的形式，改变了以往的手动操作验收。以ＲＩＣ３８６计算机为中心，以信号源如：ＳＧ５０３正弦波发生器等为标准，通过ＧＰ－１Ｂ接口总线来编程控制数字示波器，并配以打印机及绘图仪打印结果和波形，对示波器各项功能进行验收，检查仪器的各项指标是否在给定极限范围之内。初学者可根据屏幕上的提示，一步步执行，便可自动进行验收，查看结果。     

A comparative study of decision tree,random forest,and convolutional neural network for spread-F identification

Ionospheric spread-F (SF) is a commonly observed phenomenon of electron density perturbation in the F-layer. The ionospheric irregularities structure has an adverse effect on the propagation of electromagnetic waves in the ionosphere. The automatic identification of ionospheric spread-F and statistical study of the formation of spread-F are of great significance to the study of the physical mechanism of ionospheric inhomogeneity and for prediction of ionospheric irregularities. In this paper, we describe and implement three automatic identification methods of spread-F based on machine learning: decision tree, random forest, and convolutional neural network (CNN). The performance of these automatic identification methods was verified using a large set of test data. Results show that the accuracy of all three methods on identifying ionograms with spread-F exceeded 90%. After comparing the results of the three methods, we found that the decision tree method was the simplest and with the structure easiest to be understood, and it required the shortest interpretation time. In terms of the identification results, the random forest method provided better results than the decision tree method, and the CNN method was the best at accurately identifying ionograms with spread-F.     

陀螺寿命试验计算机监测设备

介绍了陀螺寿命试验计算机监测设备的设计方案。此监测设备的研制目的是为了用于在长期、连续工作条件下，自动监控多个单自由度陀螺的运转情况，完成寿命试验。在进行设备可靠性分析的基础上，给出了其硬件实现。     

飞行训练与评定系统简介

介绍了一种基于功能全部由计算机实现的新型飞行模拟研究工具－飞行训练与评定系统，其结构由模拟座舱教员台和计算机系统等部分组成，系统功能覆盖了模拟飞行，理论教学，飞行数据处理和自动评价等方面。该系统具有低成本，高可靠性，功能灵活，载剪性强，良好的开发界面和较理想的逼真度，使用维护方便等优点，可广泛应用于学校，研究机构在飞行力学，飞行控制中的人机闭环研究及学员训练。     

7150数字多用表的自动测试研究

介绍了7150数字万用表的自动化测试技术。为了提高测试工作效率,节约时间和成本,我们运用自动化编程技术,通过GPIB电缆和GPIB-USB数据采集转换卡,将数字多用表7150和多功能标准源4808相连,搭建成自动化测试系统,并采用美国NI公司的Labview软件开发平台,结合VISA(虚拟仪器软件结构)驱动技术,编制相应的自动测试程序。文中给出了测量原理、仪器的设置操作和实际的编程步骤。自动测试系统现已运用到实际工作中,其相对于手动测试,提高了测量速度和效率,测试数据量大,实用性强。