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。

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。

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。

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。

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。

基于分布式控制的多无人机协作喷洒技术

针对现有的多无人机协同中航迹规划难、造成喷洒重叠遗漏等问题,文中研究了一种优化航迹的多无人机协同精准喷洒关键技术。建立四旋翼植保无人机的动力学模型,进行动态规划算法下的模拟实验。将无人机的作业能耗和非作业能耗、药液容量、路径长度作为约束条件,尽量减少转弯次数来优化航迹。该无人机集群采用分布式结构,利用了基于节点类型的贝叶斯联盟博弈算法,来对无人机联盟结构进行动态调整,达到航迹的优化目的。该方法已成功地应用于多无人机协同精准喷洒作业中,实验验证了该方法对航迹优化的有效性。

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。

基于改进遗传算法的植保无人机姿态控制

为了解决重载荷四旋翼植保无人机位姿控制系统存在的自适应能力差、抗干扰能力弱和传统试凑法整定PID控制参数效率低等问题,提出了一种基于改进遗传算法优化的模糊PID控制算法,使控制器具备实时自优化能力,从而提升无人机的控制效果。首先,在MatLab软件中建立了四旋翼植保无人机的动力学模型和模糊PID控制算法模型;然后,采用改进遗传算法对模糊PID控制器的初始控制参数进行整定,并将优化结果与人工整定的PID控制算法所得结果进行对比。仿真实验结果表明:改进GA算法寻优后的模糊PID控制算法具有更加优良的控制效果和稳定性,有效提升了植保无人机在药物喷洒时的鲁棒性。

植保无人机在富阳区茶叶统防统治上的应用实践与思考

近年来,随着植保无人机技术的逐渐成熟,越来越多茶叶从业者将目光聚焦于应用植保无人机进行飞防施药作业。本文总结了杭州富阳区应用植保无人机开展茶叶病虫害统防统治的经验做法、取得成效,并对存在的问题提出了相应的对策建议,以期为植保无人机在茶叶病虫害防治方面提供借鉴和参考。

基于改进蚁群算法的植保无人机路径规划

针对传统蚁群算法在含障碍植保无人机路径规划中存在的易早熟、易陷入局部最优的问题,提出了一种改进蚁群算法。为降低算法陷入局部最优的概率,对启发因子进行了改进,在路径搜索的后阶段把利用贪心算法求得的从当前点到终点的距离作为新的启发因子。为提高算法的全局搜索能力,对挥发系数进行了自适应改进。采用最大最小蚁群策略对信息素浓度进行限制,避免算法早熟。仿真结果表明在复杂的作业环境下,改进蚁群算法的性能更好,具有更强的路径寻优能力。

黑龙江省北斗卫星导航系统植保无人机应用研究

我国是农业大国,黑龙江省是农业大省,农业生产是头等大事,农业植物保护工作是农业生产中重要的一个方面。对黑龙江省植保无人机的发展现状进行梳理,结合目前植保无人机普及存在的问题,提出相应的解决对策。

植保无人机在玉米病虫害防治中的应用

通过分析植保无人机在玉米种植前期、种植后以及病虫害防治后观察三个阶段的具体应用策略,展示了其精准、高效的防治优势。应用植保无人机可显著提高玉米病虫害防治的效果,为玉米生产的高产和稳产创造条件。

基于无人机植保技术的马铃薯病虫害防治方案研究

分析了植保无人机应用流程、病虫害出现前、发病中和防治后的应用技术。进行了传统人工防治方法与无人机植保技术的效果对比试验,结果表明,采用无人机植保技术在马铃薯病虫害防治效果、产量及品质上均表现出显著优势。