基于无人机航摄技术在土地整治项目中的应用研究

针对传统土地整治项目施工监管、后期监测效率不高的问题,本文通过低空无人机航摄和PhotoScan软件后期处理,对比生成的正射影像图和Google earth卫星图的分辨率和位置,发现该影像图能精准、高效的表征项目区影像数据变化,从而得到一种可用于土地整治项目各阶段动态观测的简单、快捷方法。     

Aerial seed germination and morphological characteristics of juvenile seedlings in Commelina benghalensis L.

Seed germination, seedling emergence, and the morphological characteristics of juvenile seedlings of Commelina benghalensis L. were observed. For aerial seeds collected in September and October, seedling emergence peaked in April and June for large seeds and from June to August for small seeds, whereas seedling emergence for large seeds collected in November showed peaks in March and April under natural rainfall conditions, and in April and June under irrigation conditions. Seedlings from small seeds emerged intermittently over a longer period from April to August under both conditions. Aerial seeds of C. benghalensis germinated on wet filter paper on the second day after seeding (DAS) for large seeds and the fourth DAS for small seeds. The germination percentage for large seeds was higher than that for small seeds by the 14th DAS. The germination percentage for large aerial seeds showed no significant difference between light and dark conditions. However, the percentage for small aerial seeds was higher under light than under dark conditions. Seedlings from large aerial seeds emerged on the third DAS at 0–50 mm soil depths. The percentage of emergence at 0 and 1 mm soil depths increased until the 30th DAS, whereas those at soil depths of 5–50 mm showed no change after the 9th DAS. There was no emergence at a soil depth of 100 mm. Seedlings from small aerial seeds emerged on the 6th DAS at 0–1 mm soil depths, with the percentage increasing until the 30th DAS. Although seedlings at 5 and 10 mm soil depths also emerged on the 6th DAS, there was no change in the percentage after the 12th DAS. There was no emergence at soil depths of 20–100 mm. The hypocotyl and taenia (part of the cotyledon connected to the seed) in juvenile seedlings that emerged from soil depths of 50 mm were longer than those in seedlings emerging from a soil depth of 1 mm.     

无人机施药对棉蚜的防治效果及经济效益分析

为探讨采用无人机防治新疆南部地区棉蚜的可行性并筛选防治效果好的杀虫剂及具有增效作用的杀虫剂助剂，研究了采用大疆MG-1S型无人机喷施不同的杀虫剂+助剂对棉蚜的防治效果，并对无人机飞防的经济效益进行了分析。结果表明:采用MG-1S型无人机喷施22%氟啶虫胺腈悬浮剂(SC) 225 mL/hm2(制剂量，下同)时对棉蚜的防治效果最好，优于喷施70%吡虫啉水分散粒剂(WG) 30 g/hm2和70%啶虫咪WG 60 g/hm2。在添加助剂方面，以分别在70%啶虫脒WG 60g/hm2和70%吡虫啉WG 30g/hm2中添加15 mL/hm2的高工效通用助剂的防治效果最好，其次为聚合物类助剂和飞防增效剂；而在22%氟啶虫胺腈SC(150 mL/hm2)中，以添加150 mL/hm2的飞防增效剂的效果最好，其次为矿物源类、有机硅类和聚合物类助剂。采用无人机施药，在施药后3 d和5 d的防治效果与采用机械+人工拖管施药相比均无显著性差异，但无人机田间作业施药液量减少1/3，工作效率提高3倍，机械作业费减少60元/hm2，可满足现代农业高效、节药和降低成本的需要。     

浅谈农用运输车经济效益的"挖潜增值"

农用运输车经营利润微薄,文章从技术层面入手探讨如何深挖节约潜力、降低维修费用,从而提高间接经济效益的方法措施.     

基于无人机多光谱遥感的冬小麦叶绿素含量反演及监测

旨在实现冬小麦各生育期叶绿素含量的准确估测,探究其时空变化规律。利用无人机获取冬小麦越冬期、返青期、拔节期、孕穗期和灌浆期的高分辨率多光谱图像,同时采集地面SPAD数据。选取三类光谱参数建立反演模型,优选出各生育期的最佳预测模型,并定量监测试验区冬小麦叶绿素含量时间变化和空间分布。结果表明：原始波段模型和波段倒数对数模型分别为越冬期及其他生育期叶绿素含量预测的最佳模型,拟合精度R²>0.59;时空分布上,灌浆期前试验区冬小麦叶绿素含量呈南北高、中部低特点,灌浆期则呈北高南低的趋势,叶绿素含量从越冬期到拔节期逐步增加,拔节期到孕穗期开始降低,孕穗期到灌浆期则大幅度降低。本研究建立的倒数对数预测模型,精度较高,且适用于返青到灌浆的4个生育期,对于试验区冬小麦叶绿素含量有较好的时空监测效果。     

基于状态变换法的车辆悬架系统时滞反馈控制

为了提高车辆行驶平顺性和稳定性,研究悬架系统中时滞补偿控制效果,本文以赛欧轿车悬架系统为基础,建立2自由度车辆半主动悬架系统模型,设计了时滞反馈控制器,采用理论与试验相结合的方法对系统时滞反馈控制特性进行研究。首先建立含时滞的悬架系统动力学方程,采用常微分理论和多项式判别方法分析系统稳定性,并通过时域与频域仿真对结果进行验证。研究表明:采用传统二次型最优控制律对含时滞的悬架系统进行控制,当系统控制时滞较大时,系统定性特性可能会发生改变,甚至会失稳发散。为保证系统的稳定性,采用状态变换方法设计时滞反馈最优控制律,仿真表明采用该控制律不仅可以保证系统稳定性,系统的减振特性亦有改善。最后搭建了悬架时滞反馈控制平台,基于时域辨识方法测得系统固有时滞为0.065 s,通过对相同工况下仿真结果与试验结果进行对比,发现两者具有较好的一致性,误差在15%以内,满足业内使用要求,表明研究可信,结果可为主动/半主动车辆悬架控制器实际设计应用提供参考。     

大中小型拖拉机压实对土壤坚实度和大豆产量的影响

探讨农业机械压实对土壤坚实度和产量的影响规律，对改善作物生产环境、促进农业机械化向质量型转变具有重要意义。以东北典型黑土区耕地土壤为研究对象，依照随机区组试验原理，选择大、中、小3种型号拖拉机进行6种压实处理，同型拖拉机相同压实次数试验重复3次，采用PV6.08型贯穿阻力仪测量压实轮辙截面土壤坚实度。试验结果表明：土壤坚实度随压实次数增加而逐渐递增，3种拖拉机压实测试截面浅层均出现明显压实核，且压实核内土壤坚实度随压实次数增加而逐渐增大，CASE-210型拖拉机压实对表层土壤坚实度影响程度和范围最大，压实12次时压实核处土壤坚实度达4.0 MPa，JD-280型拖拉机对深层土壤压实影响程度和范围最大，在65~80 cm的土壤深层坚实度的峰值达3.2 MPa；拖拉机压实均导致大豆产量降低，CASE-210、JD-904和JD-280拖拉机压实12次时大豆产量分别降低了21.24%、18.15%和12.38%。     

Evaluation of the pattern of spray released from a moving multicopter

BACKGROUND

Multicopters are used for releasing particulates seeds, fertilizer and spray. Their low cost and high manoeuvrability make them attractive for spraying in steep terrain and areas where overspray is undesirable. This article describes a model of multicopter wake and its influence on particulate dispersion, which is computationally economical compared to many computational fluid dynamics (CFD) approaches, yet retains reasonable accuracy.

RESULTS

A model was successfully implemented in OpenFOAM . It features source terms for the rotor wash, Lagrangian particle tracking, an evaporation model, and a porous medium approach to model the effect of the ground vegetation. Predictions were validated against the field tests of Richardson et al. which used a DJI Agras MG-1 multicopter in three different flights with airspeeds of 3.2–4.9 m s⁻¹, ground speeds of 2.1–2.9 m s⁻¹ and cross-wind speeds of 0.04–2.2 m s⁻¹. The effective swath width (30% line separation) was predicted to within one standard deviation. Sensitivity to a rotor rotational speed, flight height, flight velocity, multicopter roll and yaw angles, surface roughness length, plant height and leaf density was checked.

CONCLUSION

In all flight trials, the modelled swath was closest to the experimentally obtained swath when the surface roughness of the fetch was equal to 0.5 m (bushes) and the rotational speed of all rotors was equal to 2475 rpm with 0.75R (0.2 m) tall plant canopy (grass) introduced to the model. The model showed acceptable validity for flight velocities of ≤2.8–5 m s⁻¹ when flight parameters can be approximately estimated. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

基于动力学模型的自动引导车智能导航控制研究

提出了一种基于动力学模型的智能控制方法，将导航系统得到的信息输入智能控制器，由它输出自动引导车动力学模型所需要的控制量。因为该控制器记忆了自动引导车的动力学特性，所以使用此智能控制器的自动引导车能够较平稳地避开动态和静态障碍物。仿真实验结果表明，装有此系统的自动引导车能有效避开动态和静态障碍物，安全、可靠、平稳地驶向指定的目标，从而验证了本文提出的方法是正确和有效的。