基于相对最值点的最小二乘直线检测方法

为了解决传统目标检测中遇到的检测速度慢、精度低等问题,本文提出一种新的图像特征——相对最值点,并依据相对最值点提出一种新的最小二乘直线检测的方法。该方法首先搜索Canny边缘的闭合包络,并寻找闭合包络的相对最值点。包络上相邻相对最值点之间长度满足阈值要求的即为疑似直线的两端点,进而利用最小二乘拟合方法获得该疑似直线的拟合方差,最后利用拟合方差与拟合直线长度之比作为直线判定的标准用来检测出图像中的直线。实验表明,本方法与传统方法如PPHT直线检测、LSD直线检测方法等相比,检测直线的精度更高,检测速度更快。     

基于DDPG的单目无人机避障算法

提出了一种基于单目相机的小型多旋翼无人机的连续避障策略。所提出的方法包括深度估计和导航决策两个模块。其中,在深度估计模块采用条件对抗网络对无人机采集得到的RGB图片进行训练预处理,在导航决策模块采用深度确定性策略梯度(DDPG)算法实现无人机的连续避障。在此基础上,对DDPG中的Actor网络进行改进,通过使用多模态网络代替原有策略网络,从而抑制无人机飞行震动,提高避障能力。最后,在Airsim仿真环境中进行测试,实验表明所提算法模型经过训练能够使无人机成功躲避障碍物并到达指定目标点,与原有算法相比避障轨迹得到明显改善。     

A coupling VWM/CFD/CSD method for rotor airload prediction

A coupling fluid-structure method with a combination of viscous wake model(VWM),computational fluid dynamics(CFD) and comprehensive structural dynamics(CSD) modules is developed in this paper for rotor unsteady airload prediction. The hybrid VWM/CFD solver is employed to model the nonlinear aerodynamic phenomena and complicated rotor wake dynamics;the moderate deflection beam theory is implemented to predict the blade structural deformation; the loose coupling strategy based on the ‘delt method' is used to couple the fluid and structure solvers.Several cases of Helishape 7A rotor are performed first to investigate the effect of elastic deformation on airloads. Then, two challenging forward flight conditions of UH-60 A helicopter rotor are investigated, and the simulated results of wake geometry, chordwise pressure distribution and sectional normal force show excellent agreement with available test data; a comparison with traditional CFD/CSD method is also presented to illustrate the efficiency of the developed method.     

火箭橇体进水现象研究

在考核过载承受能力的火箭橇试验后,橇体内发现有水,从空气动力学的角度,对火箭橇体进水现象进行了初步分析,并利用FLUENT软件对进水原因进行了初步研究,通过分析,发现结构在穿越跨音速阶段时,由于内外压差的变化将导致内部或外部产生水汽。该发现为结构设计提供有益的建议。     

Global ionospheric scintillations revealed by GPS radio occultation data with FY3C satellite before midnight during the March 2015 storm

Global observations of S4 amplitude scintillation index by the GPS Occultation Sounder (GNOS) on FengYun-3 C (FY3C) satellite reveal global dynamic patterns of a strong pre-midnight scintillations in F-region of the ionosphere during the St. Patrick’s Day geomagnetic super storm of 17–19 March 2015. The observed strong scintillations mainly occurred in the low latitudes, caused by equatorial plasma bubbles. During the main storm phase (March 17), the scintillations were first triggered in the New Zealand sector near 160°E longitudes, extending beyond 40°S dip latitude. They were also enhanced in the Indian sector, but significantly suppressed in East Asia near 120°E longitude and in Africa around 30°E longitude. During the initial recovery phase (March 18–19), the global scintillations were seldom observed in GNOS data. During the later recovery phase (after March 19), the scintillations recovered to the pre-storm level in Indian, African, and American sectors, but not in East Asian and any of Pacific sectors. These results closely correlate with observations of the density depletion structures by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite, and ground-based instruments. Such consistency indicates reliability of our scintillation sensing approach even in a case-by-case comparison study. The prompt penetration electric field and disturbance dynamo electric field are suggested as the main factors that control the enhancement and inhibition of the scintillations during the storm, respectively.     

High temporal resolution global PWV dataset of 2005–2016 by using a neural network approach to determine the mean temperature of the atmosphere

Atmospheric water vapour plays an important role in phenomena related to the global hydrologic cycle and climate change. However, the rapid temporal–spatial variation in global tropospheric water vapour has not been well investigated due to a lack of long-term, high-temporal-resolution precipitable water vapour (PWV). Accordingly, this study generates an hourly PWV dataset for 272 ground-based International Global Navigation Satellite System (GNSS) Service (IGS) stations over the period of 2005–2016 using the zenith troposphere delay (ZTD) derived from global-scale GNSS observation. The root mean square (RMS) of the hourly ZTD obtained from the IGS tropospheric product is approximately 4 mm. A fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting (ECMWF ERA5) is used to obtain hourly surface temperature (T) and pressure (P), which are first validated with GNSS synoptic station data and radiosonde data, respectively. Then, T and P are used to calculate the water vapour-weighted atmospheric mean temperature (Tm) and zenith hydrostatic delay (ZHD), respectively. T and P at the GNSS stations are obtained via an interpolation in the horizontal and vertical directions using the grid-based ERA5 reanalysis dataset. Here, Tm is calculated using a neural network model, whereas ZHD is obtained using an empirical Saastamoinen model. The RMS values of T and P at the collocated 693 radiosonde stations are 1.6 K and 3.1 hPa, respectively. Therefore, the theoretical error of PWV caused by the errors in ZTD, T and P is on the order of approximately 2.1 mm. A practical comparison experiment is performed using 97 collocated radiosonde stations and 23 GNSS stations equipped with meteorological sensors. The RMS and bias of the hourly PWV dataset are 2.87/?0.16 and 2.45/0.55 mm, respectively, when compared with radiosonde and GNSS stations equipped with meteorological sensors. Additionally, preliminary analysis of the hourly PWV dataset during the EI Niño event of 2014–2016 further indicates the capability of monitoring the daily changes in atmospheric water vapour. This finding is interesting and significant for further climate research.     

现代高效刀具发展特点和产业化途径

现代高效刀具和工具工业的发展特点 1 现代高效刀具的内涵 现代高效刀具是相对传统标准刀具而言的.传统的工具工业以生产供应标准化、通用化的刀具为基本特点.长期以来,制造业有一种共识:除了少量特殊需要,尽量选用标准刀具.标准刀具虽然性能不是最优,但因经济实用而被广泛接受.但到20多年前,这种观念在发达国家开始发生变化.     

航天器安全防护保障探讨

把对航天器安全的威胁分为硬和软两大类，分析了对航天器产生威胁的类别，以及为保证航天器安全而需要采取的措施。介绍了研究的内容，需要建设的空间信息对抗系统和空间信息探测网。     

基于大数据的空管运行安全预警研究

空中交通管制的任务是确保航空器的安全飞行,为了保证飞行安全,需要进行空中交通管制系统运行安全评估及预警的研究.借鉴大数据理论建立空中交通管制大数据概念,从影响空中交通管制系统运行的主要风险因素出发,建立空中交通管制安全运行的状态向量空间,利用主成分分析法去除基础向量线性相关性,再利用聚类分析过程建立空中交通管制运行安全预警知识库,实现空中交通管制运行安全评估和及时预警.结果表明:所用的预警分类分析方法能够很好地实现预警分类和安全评估,为管制部门的相关决策提供理论依据.