Large scale sand saltation over hard surface:a controlled experiment in still air

Saltation is the major particle movement type in wind erosion process. Saltating sand grains can rebound up to tens of times larger in length and height over hard surface(such as gravel surface) than over loose sand surface. Gravels usually have different faces, causing distinct response of the impacting grains, but the effects of the grain and gravel-surface contact angle on grain rebound are not yet well quantified. We performed full-range controlled experiments of grain saltation using different contact angles, grain sizes and impact speeds in still air, to show that contact angle increases the height of representative saltation path but decreases particle travel length. The results were compared with outputs from the COMprehensive numerical model of SALTation(COMSALT). Large saltation height of 4.8 m and length of 9.0 m were recorded. The maximum and representative saltation height over the gravel surface were found to be about 4.9 times and 12.8 times those over the loose sandy surface, respectively. The maximum saltation length may be reduced by 58% and the representative saltation height may be increased by 77% as contact angle increases from 20° to 40°. We further showed that the collision inertia contributes 60% of the saltation length, and wind contributes to the other 40%. These quantitative findings have important implications for modeling saltation trajectory over gravel surface.     

基于SLAM的无人机飞行参数设定方法研究#br#

为克服无人机林间飞行环境复杂、作业多样化、点云数据质量难以评价等导致的飞行参数不合理、点云数据质量差的问题,提出一种基于同时定位与建图(Simultaneous Localization and Mapping,SLAM)的无人机林间环境飞行参数设定方法。首先使用三维激光雷达所采集的林间点云数据进行建图,然后通过建图轨迹与GNSS-RTK数据轨迹进行对比分析,评价点云数据的质量,最后根据其均方根误差对无人机的最佳飞行高度与速度参数进行设定。分析结果表明：飞行速度固定时,机载激光雷达飞行轨迹的均方根误差与飞行高度成正相关。飞行高度固定时,机载激光雷达飞行轨迹的均方根误差与飞行速度成正相关。在平均高度为6~7 m,长度为100 m的林间,无人机的最佳飞行高度为12 m,最佳飞行速度为2 m/s,均方根误差为1.262 m。该方法满足评价点云数据质量的需求,同时为无人机林间环境飞行参数的设定提供理论支撑。     

Windborne migration routes of newly-emerged fall armyworm from Qinling Mountains–Huaihe River region,China

The fall armyworm(FAW, Lepidoptera: Noctuidae), Spodoptera frugiperda(J. E. Smith), invaded China in mid-December 2018; since then, it has become a great threat to Chinese agricultural production. Qinling Mountains–Huaihe River region(QM–HRR) is the transitional zone between northern and southern China, an important region for both corn and wheat production. Based on the actual occurrence of QM–HRR invaded by FAW in 2019, daily mean surface air temperature and nocturnal wind conditions at 925 hPa were examined, and migratory routes of FAW moths originated in QM–HRR were modeled by a forward-trajectory-analysis approach. The results indicated that migratory activities of FAW adults emerged in QM–HRR were initiated from late June. The moths from western QM–HRR, where has complex topographic terrain, mainly flied to Ningxia and Inner Mongolia before mid September. However, FAW moths from the eastern QM–HRR primarily engaged in high-altitude northward transport assisted by the prevailing southerly winds before mid August, and the North China Plain was identified as the main destination of FAW. Meanwhile, the migration trajectories of FAW moths had a possibility to reach the Northeast China Plain. From mid August, FAW moths in eastern QM–HRR largely migrated southward and returned to the Yangtze River Valley. This study provides detailed information on the occurrence and migration routes of FAW moths from QM–HRR and will be helpful for early warning and development of integrated pest management strategies for the control of this exotic insect pest.     

Case study on the first immigration of fall armyworm,Spodoptera frugiperda invading into China

The fall armyworm(FAW), Spodoptera frugiperda is one of the most damaging crop pests, and it has become major threat to the food security of many countries. In order to monitor possible invasion of this pest into China, a searchlight trap was established in March 2018 in western Yunnan Province, China, where it has served as the "first station" for many pests that have migrated from Myanmar to China. A number of suspected FAW moths were captured and identified by DNA sequencing. The results showed that the FAW moth was first captured on December 11 and formed its first immigration peak in mid-December 2018. DNA detection revealed that the early invading FAW population was the "corn-strain". The field survey indicated that the pest mainly colonized corn in Pu'er, Dehong and Baoshan areas. Migration trajectory simulation implied that the moths might have mainly come from the eastern area in the mid-latitude region of Myanmar(20–25°N, 94–100°E). This case study confirmed the first immigration of FAW into China, and will be helpful for guiding monitoring and management work to control this pest.     

多约束条件下某智能飞行器航迹快速规划

以某智能飞行器为研究对象,研究复杂环境下航迹快速规划.为校正系统结构限制所带来的定位误差,使得智能飞行器能按照预定的航迹完成任务,基于多约束条件最优化理论,采用遗传算法扩展而来的NSGA-Ⅱ(非支配排序遗传算法)算法进行航迹规划.结果表明,基于NSGA-Ⅱ,使用交叉行为和变异行为将初始解进一步筛选优化并最终得到最优解....     

带农具拖拉机地头转弯最佳路径设计

拖拉机在进行田间作业时,其自动行驶控制主要包含轨道设计和沿着所给轨道行驶的追踪控制两个方面.本研究采用最优控制理论,设计了带农具拖拉机利用前进挡工作时进行地头转弯的最佳路径.程序运行结果表明,其计算时间短,能够保证拖拉机自动行驶控制时的实时控制.     

基于逆运动学降维求解与YOLO v4的果实采摘系统研究

为提高采摘设备的执行效率,采用六自由度机械臂、树莓派、Android手机端和服务器设计了一种智能果实采摘系统,该系统可自动识别不同种类的水果,并实现自动采摘,可通过手机端远程控制采摘设备的起始和停止,并远程查看实时采摘视频。提出通过降低自由度和使用二维坐标系来实现三维坐标系中机械臂逆运动学的求解过程,从而避免了大量的矩阵运算,使机械臂逆运动学求解过程更加简捷。利用Matlab中的Robotic Toolbox进行机械臂三维建模仿真,验证了降维求解的可行性。在果实采摘流程中,为了使机械臂运动轨迹更加稳定与协调,采用五项式插值法对机械臂进行运动轨迹规划控制。基于Darknet深度学习框架的YOLO v4目标检测识别算法进行果实目标检测和像素定位,在Ubuntu 19.10操作系统中使用2 000幅图像作为训练集,分别对不同种类的果实进行识别模型训练,在GPU环境下进行测试,结果表明,每种果实识别的准确率均在94%以上,单次果实采摘的时间约为17 s。经过实际测试,该系统具有良好的稳定性、实时性以及对果实采摘的准确性。     

林木采伐机工作臂的工作轨迹

分析了林木采伐机工作臂的结构组成.在Solidworks环境下建立工作臂三维模型,绘制液压控制系统原理图;通过动臂动作优先规划对工作臂三维运动进行仿真,确定工作油缸行程范围及工作臂运动轨迹,并准确反映工作臂实际运动情况.     

Stand Density Control Diagrams for Scots pine and Austrian black pine plantations in Bulgaria

Stand Density Control Diagram (SDCD) is a stand-level mathematical model, which describes the relationships between yield, density and mortality throughout all stages of stand development. The SDCD is primarily used to derive density control schedules by management objectives. The main objectives of the present study are to define a modified model of SDCD for application to Scots pine (Pinus sylvestris L.) and Austrian black pine (Pinus nigra Arn.) plantations in Bulgaria, to examine the fitness of the model with representative experimental data sets from plantations of both species and to present a way of direct application of the SDCDs for practical purposes. The constructed SDCDs characterize the spatial-temporal dynamics of the pine plantations in a broad range of densities, forest sites and growth stages from 4 to 26 (28) m of dominant height class. The full density lines were fixed with self-thinning exponents α = 1.69 and α = 1.75 for Scots pine and Austrian black pine, respectively, and the trajectories of natural thinning for 23 initial densities (444-40000/ha) were determined. A direct way for application of the SDCDs to the plantation management was designed to estimate the optimal initial densities for the maximum attainable final yield and large-size wood production by self-thinning stands.     

Production Planning Method for Steelmaking-continuous Casting Process Based on Time Backward and Process Simulation

Reasonable production planning effectively ensures smooth operation. According to the analysis of the characteristics of steelmaking-continuous casting production process, a production planning method for steelmaking - continuous casting process based on time backward inference method and process simulation is presented. Production plan meeting certain criteria is rapidly gained by time backward inference method, and is regarded as input of simulation model in steelmaking process. Considering time randomicity in production process and transporting equipment restriction, production plan meeting more restrictive conditions, such as no equipment conflict, continuous casting, and etc, is acquired through simulating. It assures that the plan is carried out in practice. The instance demonstrates the feasibility of the method.