Particle Kinematics Analysis of Droplet Drift in Spraying Operation of Plant Protection UAV

[Objectives]The paper was to study the effect of droplet drift on spray quality of plant protection UAV.[Methods]Based on the theory of multiphase flow and the method of particle kinematics,the force and motion trajectory of droplet sprayed by plant protection UAV were theoretically analyzed and mathematically modeled.On the basis of the assumption of wind speed in the ground layer and the laminar sublayer,that is,it is assumed that the wind speed in the area of wind measurement was approximately a linear distribution,the coupling iterative solution of the equations was carried out.The influence of droplet diameter,flight height,flight speed of plant protection UAV,course angle,wind speed,wind direction,initial droplet velocity and direction of initial velocity on droplet drift were analyzed.The influence of the coupling effect of each factor on droplet drift was further discussed and the distribution of droplet drift concentration was obtained.[Results]The wind speed and direction had much influence on the drift distance of droplets,and the drift distance and the initial velocity angle show a quadratic function distribution.Under the given conditions,the drift distance was the closest when the initial velocity angle was about 20°.The droplet drift was mainly distributed scatteredly around the nozzle.[Conclusions]The study provides a reference for improving the spraying quality of plant protection UAV.

Design and Research of Efficient Adaptive Spray Plant Protection UAV

When the plant protection UAV is spraying on plants, the operator usually performs visual inspection on the vertical distance between the UAV and the plant to adjust the spray height to complete the application. Visual inspection by human eyes is easy to cause the error of spray deposition and deposition density. In order to improve the full utilization of drugs and the spraying efficiency of plant protection UAV, an efficient adaptive spray plant protection UAV was designed, and the vertical distance from the UAV to the plant was collected by ultrasonic wave. Meantime, the plant density was detected in real time, and the flight attitude of plant protection UAV and application rate of spray nozzle were automatically adjusted. The experimental results showed that the designed highly efficient adaptive spray plant protection UAV had fast response speed, precise spray location and less drug loss.

Application of MR Technology in Teaching:A Case Study of UAV Agriculture&Forestry Plant Protection Curriculum

In order to solve the problems of insufficient training equipment,relatively lack of curriculum resources and single teaching means in the teaching of UAV(unmanned aerial vehicle)applied technology major,this paper studies the application of MR(Mixed Reality)in UAV applied technology major teaching,with the teaching of UAV agriculture&forestry plant protection curriculum as the carrier.The study will solve the pain points in teaching,improve the teaching ability and teaching information level,and increase the talent training quality of UAV,agriculture&forestry plant protection and related majors.Furthermore,it will create a protective,interactive,remote and scalable teaching experience for stu-dents,which can improve the teaching effect and reduce the teaching cost.

Downwash airflow field distribution characteristics and their effect on the spray field distribution of the DJI T30 six-rotor plant protection UAV

Spray characteristics are the fundamental factors that affect droplet transportation downward,deposition,and drift.The downwash airflow field of the Unmanned Aviation Vehicle(UAV)primarily influences droplet deposition and drift by changing the spray characteristics.This study focused mainly on the effect of the downwash airflow field of the UAV and nozzle position on the droplet spatial distribution and velocity distribution,which are two factors of spray characteristics.To study the abovementioned characteristics,computational fluid dynamics based on the lattice Boltzmann method(LBM)was used to simulate the downwash airflow field of the DJI T30 six-rotor plant protection UAV at different rotor rotational speeds(1000-1800 r/min).A particle image velocimetry system(PIV)was utilized to record the spray field with the downwash airflow field at different rotational speeds of rotors(0-1800 r/min)or different nozzle positions(0,0.20 m,0.35 m,and 0.50 m from the motor).The simulation and experimental results showed that the rotor downwash airflow field exhibited the‘dispersion-shrinkage-redispersion’development rule.In the initial dispersion stage of rotor airflow,there were obvious high-vorticity and low-vorticity regions in the rotor downwash airflow field.Moreover,the low-vorticity region was primarily concentrated below the motor,and the high-vorticity region was mainly focused in the middle area of the rotors.Additionally,the Y-direction airflow velocity fluctuated at 0.4-1.2 m under the rotor.When the rotor airflow developed to 3.2 m below the rotor,the Y-direction airflow velocity showed a slight decrease.Above 3.2 m from the rotor,the Y-direction airflow velocity started to drastically decrease.Therefore,it is recommended that the DJI T30 plant protection UAV should not exceed 3.2 m in flight height during field spraying operations.The rotor downwash airflow field caused the nozzle atomization angle,droplet concentration,and spray field width to decrease while increasing the vortex scale in the spray field when the rotor system was activated.Moreover,the increase in rotor rotational speed promoted the abovementioned trend.When the nozzle was installed in various radial locations below the rotor,the droplet spatial distribution and velocity distribution were completely different.When the nozzle was installed directly below the motor,the droplet spatial distribution and velocity distribution were relatively symmetrical.When the nozzle was installed at 0.20 m and 0.35 m from the motor,the droplets clearly moved toward the right under the induction of stronger rotor vortices.This resulted in a higher droplet concentration in the right-half spray field.However,the droplet moved toward the left when the nozzle was installed in the rotor tip.For four nozzle positions,when the nozzle was installed at 0 or 0.20 m from the motor,the droplet average velocity was much higher.However,the droplet average velocity was slower when the nozzle was installed in the other two positions.Therefore,it is recommended that the nozzle is installed at 0 or 0.20 m from the motor.The research results could increase the understanding of the downwash airflow field distribution characteristics of the UAV and its influence on the droplet spatial distribution and velocity distribution characteristics.Meanwhile,the research results could provide some theoretical guidance for the choice of nozzle position below the rotor.

基于改进ESKF的植保无人机时延位姿补偿算法

为解决全球导航卫星系统和惯性测量单元融合时间不同步问题,提高植保无人机位姿估计精度,本文根据植保无人机大惯性、强振动的特性提出一种基于改进误差状态卡尔曼的时延位姿补偿算法。首先对名义状态变量线性预测,引入渐消因子提高强振动环境下的系统稳定性;接着采用互补滤波对角速度补偿,对姿态误差状态变量修正;最后结合测量的延迟时间,使用互补滤波外推数据,提高大惯性特性下的速度位置精度。实验结果表明,相较于误差状态卡尔曼算法,横滚角和俯仰角均方根误差减少0.2669°和0.2414°,偏航角均方根误差减少0.0764°;正常航迹植保作业下,东北天方向速度均方根误差减少0.2105、0.1849、0.2388 m/s;东北天方向位置均方根误差分别减少0.21、0.19、0.23 m,有效提高位姿估计精度。

基于迭代算法分析的无线通信信号识别研究

为进一步提升我国植保无人机通信系统的作业效率,基于迭代计算思维,针对其无线通信信号的识别与处理模块展开分析。以通信路径原理为基础,以通信信道资源识别、功率改进为切入点,搭建准确的通信迭代计算模型,进行特性分析与关联匹配设置,并展开整机通信作业参数试验效果验证。结果表明:基于迭代算法分析的无线通信信号识别与处理各模块功能运行稳定,信号时延率与信道误码率均相对降低,通信的识别准确率相对提升8.94%,整体通信综合效率提升至96.93%。此迭代算法分析准确,设计效果明显,对于类似智慧型农机装备的通信质量与通信效率提升有较好的参考价值。

广西产区柑桔溃疡病和柑桔全爪螨同治降本增效技术研究

柑桔全爪螨(俗称红蜘蛛)和柑桔溃疡病是广西沃柑生产上防控用药量最大的两种病虫害。为探索同时防治这两种病虫害的综合技术方案,从而达到降本增效的目的,设计了99%矿物油乳油∶77%氢氧化铜可湿性粉剂∶80%代森锰锌可湿性粉剂=5∶1∶2混配的“油铜锰方案”,并且3—7月在田间开展丰田FT-18型背负式电动喷雾器人工喷雾、极目EA-30XP农业无人机常量飞防和推荐施药量减量30%飞防不同施药方式的对比试验。试验表明,采用“油锰铜方案”防治柑桔红蜘蛛和柑桔溃疡病时,常量飞防和减量飞防的防治效果不低于人工喷雾,有些时期甚至更好。“油锰铜方案”减量飞防对柑桔红蜘蛛的防治效果最高可达97.71%,对柑桔溃疡病的防治效果可达98.57%。“油锰铜方案”减量飞防可实现“一高三减”的效果,即每小时10×667 m^(2)的高施药工效、减少用水量94%、减少人工成本33.33%和减少农药使用量37.5%。“油锰铜方案”减量飞防能有效解决广西沃柑产区柑桔溃疡病、柑桔红蜘蛛“一病一虫”施药难、防治效果差和防治成本高的难题,可在地势平坦的柑桔产区大面积推广应用。

基于相邻争夺算法的无人机多架次植保作业路径规划

为了提高植保无人机作业效率,减少无人机作业损耗,该研究针对传统粒子群优化(particle swarm optimization,PSO)算法在规划植保作业路径时容易陷入局部最优,能耗最优方案的搜索能力低下等问题,该研究提出一种基于相邻争夺(adjacent competition, AC)算法的植保无人机作业路径规划算法。首先,对所有粒子设置作业距离范围,以防止单次作业距离过长或过短的极端情况;其次,在作业距离范围内随机分配每个粒子的作业距离,作为搜索的初始值;最后,相邻粒子相互争夺作业距离间接改变各架次作业距离,搜索出最优路径。相邻争夺算法保证了植保无人机作业总距离一定,对搜索方向进行先验且保证特殊点不被遗漏,避免算法陷入局部最优解。使用Matlab软件对420 m×200 m的模拟植保场地进行算法仿真验证,传统粒子群算法常陷入局部最优解,在10次规划中相较于遍历出的能耗最优规划方案增加了16.16%~38.14%的能耗,本文提出的相邻争夺算法规划结果的能耗远低于传统粒子群算法,算法具有更强的搜索能力。使用RflySim仿真平台搭建植保无人机模型和420 m×200 m的作业场地,在虚拟环境下比较传统粒子群算法与相邻争夺算法规划结果的模拟跟踪情况,相邻争夺算法规划结果的能耗相较传统粒子群算法减少了25.15%。420 m×200 m作业场地实际飞行试验中,相邻争夺算法规划结果的能耗相较传统粒子群算法减少了34.48%,更适应多架次植保作业。

植保无人机烟草大田施药作业参数优选

为探究当前主流植保无人机作业参数对烟草大田不同时期雾滴沉积分布规律的影响,获得雾滴最佳分布效果,以电动多旋翼植保无人机为对象,采用三因素三水平的正交试验对植保无人机飞行高度、飞行速度、施药量3个作业参数优化组合,同时对植保无人机的田间有效喷幅进行检验。结果表明:(1)在烟草伸根期最佳作业参数为飞行高度3 m、飞行速度4 m/s、施药量15 L/hm^(2);(2)在烟草旺长期最佳作业参数为飞行高度3 m、飞行速度5 m/s、施药量15 L/hm^(2);(3)在烟草成熟期最佳作业参数为飞行高度5 m、飞行速度4 m/s、施药量30 L/hm^(2);(4)植保无人机在烟草上的作业喷幅宜设为3~4 m。该试验结果可为后续植保无人机在烟草不同生长期的病虫害防治提供理论基础。

基于Fluent的重载植保无人机雾滴沉积特性的研究

以有效载荷为135kg的FBH-300T纵列式重载油动双旋翼无人机为研究对象,测量了飞机旋翼风场和喷头数据,并使用Fluent建立喷头在外流场中的仿真模型。采用计算流体力学(Computer Fluid Dynamic,CFD)的方法,对FBH-300T无人机飞行速度、侧风和载荷对飞机施药过程中雾滴沉积的影响进行了仿真计算和试验验证。结果表明:植保无人机的飞行速度、侧风和载荷都会影响雾滴的沉积分布,雾滴沉积受侧风的影响最大,其次为飞行速度,受载荷的影响最小;在0~2m/s的侧风和0~5m/s的飞行速度范围内,雾滴的穿透性和漂移变化不大;飞机从满载到空载的施药过程中,雾滴沉积特性基本不发生变化,符合田间试验结果。由此证明:使用Flu-ent开展植保无人机雾滴沉积特性的相关研究是可行的,能够为植保无人机雾滴漂移、运动及沉积研究提供参考。

植保无人机精准喷施方法研究综述

作为一种新兴农业技术,植保无人机以其高效、精准、灵活等特点在农作物疾病和虫害防治中具有重要意义。综述了植保无人机精准喷施方法的关键技术,包括植保无人机发展现状、路径规划算法、喷施器研究和漂移控制。通过对相关文献的分析和整理,总结了植保无人机路径规划算法的特点和应用情况,重点介绍了经典路归算法、遗传算法以及蚁群优化等元启发算法的优点和不足,以及喷施器研究和漂移控制研究的进展和挑战。最后,提出了未来研究的方向和建议,包括改进算法性能、优化路径规划策略、提高喷施器的精度和稳定性、优化漂移控制算法等。旨在为相关研究者提供全面的研究概览,推动植保无人机精准喷施技术的进一步发展和应用。

基于CFD仿真植保无人机在各工况下对施药效果的影响

为探究多旋翼植保无人机在不同工况下对施药效果的影响,明确两款多旋翼植保无人机结构设计优缺点,规范植保无人机在飞防作业中的参数设置。试验以两款多旋翼植保无人机为对象,采用CFD仿真模拟植保无人机在不同工况下的流场分布、风场幅宽、飘移情况。结果表明:两款植保无人机主要风场幅宽可达6~12 m,次要风场幅宽可达12~20 m;增加飞行高度、飞行速度可以获得较大的喷洒面积,但风场穿透力减弱、雾滴飘移距离增加,顺风作业有利于改善施药效果;四旋翼植保无人机相较于六旋翼植保无人机平衡性更好,下压力及抗飘移能力都有一定优势,且风场分布均匀规整,更有利于喷洒均匀。可为后续植保无人机机型结构优化提供思路和为植保无人机飞防作业参数设置提供理论依据。

基于语音识别处理的植保无人机航行路径控制研究

设计了基于HMM的语音识别处理算法,分析了植保无人机的结构与工作原理,并利用改进人工势场法对植保无人机的飞行控制和航行轨迹规划进行分析了研究。试验结果表明:语音控制控制准确度非常高,达到了90%及以上;植保无人机航行路径控制准确,能够成功避开障碍物,并动态规划最优飞行路径。

不同类型植保无人飞机施药作业对烟草植株的影响

为规范植保无人飞机防治烟草病虫害的技术应用,评估了植保无人飞机在烟草病虫害防治过程中对烟株的安全性,并筛选出适合烟株生长中后期飞防施药的植保无人飞机类型及飞行方式。本试验选用目前主流的9种不同类型的植保无人飞机,分析对比了9种植保无人飞机在烟草成熟期进行飞防作业时对烟草植株形态的影响。结果表明,烟草植株成熟期采用四旋翼植保无人飞机以4 m或3 m的飞行高度垂直于烟草种植垄作业对烟草的损伤较低。

玉米不同生育期多旋翼植保无人机防治草地贪夜蛾施药参数优化

【目的】比较多旋翼植保无人机在玉米不同生育期施药参数对作业质量和草地贪夜蛾(Spodoptera frugiperda)防治效果的影响,筛选最佳施药参数,为草地贪夜蛾精准用药提供科学依据。【方法】以大疆T20型六旋翼植保无人机为对象,分别在玉米大喇叭口期和抽穗期对作业高度、作业速度和喷头型号进行沉积分布优选试验以及调查药后7 d玉米上草地贪夜蛾的虫口减退率和防治效果。【结果】玉米大喇叭口期:当无人机飞行速度为4 m/s、高度为2.5 m、喷头型号为SX110015VS时,雾滴归一化平均沉积量最高为0.45μL/cm^(2);当无人机飞行速度为4 m/s、高度为1.5 m、喷头型号为SX110015VS时,雾滴密度和覆盖率平均值均最高、分别为44.92个/cm^(2)和9.31%。玉米抽穗期:当无人机飞行速度为4 m/s、高度为2.5 m,喷头型号为SX110015VS时,雾滴归一化平均沉积量、雾滴密度和覆盖率平均值均最高,分别为0.50μL/cm^(2)、82.92个/cm^(2)和7.67%。【结论】在玉米大喇叭口期和抽穗期施药参数选择时需结合田间实际病虫害发生情况,当无人机飞行速度为4 m/s、飞行高度为2.5 m,喷头型号为SX110015VS时,雾滴沉积量均最高,且施药后7 d对草地贪夜蛾的校正防效均在85%以上。

植保无人机喷施化学封顶剂不同作业参数对棉花冠层雾滴沉积的影响

为探索植保无人机化学封顶作业的雾滴沉积特征,本研究开展了添加助剂和无助剂的植保无人机不同作业参数的两组田间试验,每组采用两因素裂区试验设计,无人机作业高度为主区(2.0 m、2.5 m、3.0 m、3.5 m,以H1、H2、H3、H4表示),无人机飞行速度为副区(3 m s、5 m s、7 m s,以V1、V2、V3表示),测定棉花冠层上、中、下部叶片雾滴密度、雾滴沉积量和雾滴粒径特征,评价飞喷作业效果。结果表明1)上部冠层中,H2V2的雾滴密度最大,其次是H1V1,平均雾滴密度助剂组较无助剂组高21.78%;雾滴沉积量以H2V2最大,助剂组达0.3833μL cm^(2),无助剂组达0.2667μL cm^(2);H3V2、H4V1和H2V2的雾滴相对粒径谱宽度显著小于其他处理,且其助剂组的明显低于无助剂组;2)中部冠层中,H2V2的雾滴密度及雾滴沉积量最大,其次是H3V1,平均雾滴密度及助剂组雾滴沉积量较无助剂组高52.80%和123.12%;雾滴相对粒径谱宽度助剂组以H3V1最低,无助剂组以H4V3最低,其平均值助剂组较无助剂组低7.62%;3)下部冠层中,H2V2的雾滴密度最大,其次是H1V1,平均雾滴密度助剂组较无助剂组高69.10%;雾滴沉积量助剂组以H2V2最大,其次是H3V1,无助剂组以H1V1最大,其次是H2V2,其平均值助剂组较无助剂组低93.73%;雾滴相对粒径谱宽度助剂组以H2V1最低,无助剂组以H4V1最低,其平均值助剂组较无助剂组低9.10%;4)雾滴密度和雾滴沉积量随冠层加深而降低,雾滴相对粒径谱宽度则差异不大。冠层雾滴沉积总量以H2V2最大,助剂组达0.8343μL cm^(2),无助剂组为0.4221μL cm^(2),各部分雾滴沉积量CV值,助剂组以H2V2最小,无助剂组以H1V2和H2V2较小。综上所述,添加助剂且无人机作业高度为2.5 m、速度为5 m s时群体雾滴沉积量及均匀性最大,雾滴穿透性最强,可作为实际应用的参考。

提升水稻上植保无人机喷施药液沉积效果的关键因素

旨在解决植保无人机在水稻上施药后存在雾滴分布不均、农药沉积率不高等实际田间作业问题,比较分析了飞防助剂、施药液量、飞行速度对植保无人机在水稻上施药后雾滴分布和农药沉积率的影响,明确可产生显著性差异的关键因素,进一步分析该因素是否影响农药混配药液的微粒物理性质和润湿性能。结果表明:在三因素三水平的正交试验中,不同试验处理在上层收集的雾滴的面积显著大于中层和下层,加入助剂促使试验处理在不同高度上的雾滴分布较为均匀,它们在中、下层收集的雾滴的面积占比明显得到提高;飞防助剂、施药液量和飞行速度可不同程度地影响农药沉积率,农药沉积率范围在43.72%~68.63%;体现3个因素对农药沉积率影响程度的R值分别为13.44、6.25和4.93,其中仅飞防助剂产生的差异达显著性水平;在药液混配后0~48 h内,加入2种不同助剂均可显著降低其表面张力和静态接触角,加入2种不同助剂的药液之间则未表现显著差异;此外,呈现较高农药沉积率的助剂品种则可同时有效降低药液在混配后0~48 h内的粒径大小和粒径分散程度。研究结果对于植保无人机在水稻上的精准施药技术提升具有重要参考依据,可以提高农药沉积率,减少农药流失。

基于深度学习的植保无人机识别系统应用研究

针对人工识别病虫害种类并定位的方法精度低、速度慢且人工成本巨大的问题,基于深度学习对植保无人机的识别系统应用进行研究。该识别系统主要包括3层,分别是感知层、传输层和应用层。为使植保无人机能够准确地识别病虫害种类并定位,采用深度学习算法进行人工智能识别,并对卷积神经网络和识别的评价指标进行了设计。为验证该识别系统的性能,进行了训练和测试试验及系统在其他数据集的测试试验。试验结果表明:系统的病害识别率较高,且具有良好的可移植性。

风场扰动下植保四旋翼无人机的建模与控制

由于四旋翼植保无人机的飞行高度较低,在实际飞行中易受到环境风场的影响。为此,根据Newton-Euler方程建立了风场环境下四旋翼飞行器的动力学模型,并设计了基于内外环PID控制策略的控制器。其中,姿态角控制器采用基于四元数的反馈控制器,并使用Lyapunov稳定性判据验证了其全局渐近稳定性;姿态角速率控制器采用PID控制器;位置控制器由速度PID控制器和位置P控制器组成。通过在Gazebo中进行风场模拟仿真实验和实际飞行试验,对设计的四旋翼飞行器控制系统进行参数调试和验证,结果表明:控制器具备在风场环境下控制四旋翼无人机稳定飞行的能力。

耦合风场四旋翼植保无人机下洗流与雾滴分布研究

旋翼植保无人机喷药过程中雾滴与旋翼旋转产生的下洗流场和外界风场高度耦合作用,直接影响施药品质。因此基于拉格朗日多相流模型对耦合风场的四旋翼植保无人机下洗流、有无下洗雾滴分布和含风场雾滴分布规律进行数值分析计算,通过旋翼风速测量试验验证数值计算方法的可靠性。结果表明,旋翼下洗气流在轴间中垂线上互相吸引,会发生气流聚合现象,最大气流速度为14 m/s;随着风场作用,迎风侧气流受到挤压逐渐向背风侧偏转,风速过大超过3 m/s下洗流已逐渐失去对风抗干扰能力;有下洗气流作用时沉积时间相比无下洗流作用时加快10倍,提高施药效率;风速的增加导致雾滴的沉积范围变大,当风速达到2~3 m/s时漂移增加,出现复喷现象更加严重。