旋翼式无人机授粉作业冠层风场分布规律

为提高杂交水稻机械化种植效率,扩大父母本种植行宽比,采用旋翼式无人机进行辅助授粉作业。旋翼风场是由无人机旋翼旋转推动空气进行流动作用在作物冠层而形成。风场的覆盖宽度、风场内各方向风速的大小以及风场的分布规律将会直接影响到农用无人机田间作业的效果。该文结合无人机的飞行参数使用风速参数采集系统获取18旋翼无人机的授粉作业风速,其中对于矩阵数据(100×60)的行数据和列数据的意义进行了充分的讨论,总结了行、列数据的特点并结合试验实际情况对数据进行处理。发现3向风速数据的时序变化规律保持有一致性,X向风速在最大值时刻之前其平均值要大于Y向与Z向风速;X向、Y向风速值时序曲线之间的形状特征差异小于X向与Z向或者Y向与Z向之间的形状特征差异。而从3向风速值的空间变化分布情况也可看出无人机飞行轨迹与传感器行阵列交汇点处(9#~11#)所采集风速平均值最大,考虑到测量误差值,随着采样点距离飞行轨迹越远,采样点对应风速值衰减越多。综合二维风场数据可知3向风场宽度对比结果为Y向X向Z向。在此基础上,采用高斯法拟合等方式对行数据及列数据进行计算,通过对比各统计项的参数,拟合列数据建立风速数据与时间关系的5阶指数函数模型;拟合行数据作为风速数据与采样点分布距离关系的6阶指数函数模型。利用矩阵变换基于行、列数据模型最终建立水稻冠层处无人机旋翼X向二维风场理想模型,且由模型图中可发现无人机沿冠层飞行时旋翼X向风场的分布形状存在"陡壁"效应,即无人机旋翼下风速达到最大值,前向风速增大率要明显高于后向减小率,整个风场"陡壁"沿无人机飞行方向左右对称。研究将为无人机辅助授粉通过改变风场实现新的作业方法提供参考。

Distribution of canopy wind field produced by rotor unmanned aerial vehicle pollination operation

Abstract: In order to improve the efficiency of hybrid rice planting mechanization and expanding the row width ratio of the parents planting, rotary-wing UAV (unmanned aerial vehicle) is used to the supplementary pollination work. Rotor wind is driven by UAV rotor rotating, which propels the air flow in crop canopy and forms wind field. Cover width of wind field, wind speed in 3 directions and distribution of wind field will directly affect the agricultural UAV's field effect. In this paper, based on the UAV flight parameters, wind speed acquisition system was used to collect pollination's wind speed of 18-rotor UAV; for wind data, the significance of the row and column data of matrix data (100×60) was fully discussed, and the characteristics of row and column data were summarized and it was processed with the field test. The temporal change law of the wind speed data in three directions has the characteristics of consistency, and the average value of X direction is greater than Y and Z direction before the maximum moment; the difference of the wind speed value sequence curve between X and Y is less than the differences between X and Z or Y and Z. The space distribution of wind speed values in 3 directions suggests that the maximum average value of collected wind speed occurs in the intersection of UAV flight path and a sensor array (9#-11#); considering the error of measurement value, the farther the distance between the sample point and flight path, the more the attenuation of corresponding wind speed value of sampling points. Summarizing two-dimensional wind field data, it is found that the result of the wind field widths in 3 directions is Y>X>Z. On this basis, the method of Gaussian curve fitting is used to calculate the row data and column data; by comparing the statistical parameters, column data is fitted to establish the five-order exponent function model of the relationship between wind speed data and time, and row data is fitted to establish the six-order exponent function model of the relationship between wind speed data and sample point. The method of matrix transformation is used to eventually establish the ideal 2-dimensional wind field model in UAV rotor X direction in rice canopy based on row and column data models. And by the model diagram, it is found that "steep" effect exists in the distribution shape of wind field in X direction, which means the maximum wind speed is below the rotor drones, the increasing rate of the wind speed in forward direction is significantly higher than the reducing rate of backward direction, and the wind field "steep" presents bilateral symmetry along the UAV flight direction. "Steep" effect and the model parameters are used to clarify the shape of the distribution of UAV rotorcraft wind field in rice canopy plane. Then we can study how to use independent air source or auxiliary device to change the existing wind field distribution shape to improve pollination effect. The new method provides the theoretical foundation for the UAV pollination work. It must be noted that the model is only a single sample from a single-direction data, and only the ideal basic model of wind field distribution of UAV rotorcraft in the canopy, and the further researches are needed for one-direction model of the UAV rotorcraft wind field.