Li Longlong, Zhang Ruirui, Chen Liping, Liu Boqin, Zhang Linhuan, Tang Qing, Ding Chenchen, Zhang Zhen, Hewitt Andrew J
Research Center of Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing, China.
National Research Center of Intelligent Equipment for Agriculture, Beijing, China.
Front Plant Sci. 2022 Jul 18;13:939733. doi: 10.3389/fpls.2022.939733. eCollection 2022.
Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination ( > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift.
喷雾漂移是农业植物保护作业不可避免的结果，一直是喷雾应用行业主要关注的问题之一。喷雾漂移评估对于合理选择喷雾技术和工作环境至关重要。如今，在漂移评估中使用被动收集器的传统采样方法复杂、耗时且 labor-intensive。本文的目的是提出一种基于三维激光雷达传感器评估喷雾漂移的方法，并测试被动收集器替代方案的可行性。首先，基于三维激光雷达的点云数据建立了漂移测量算法。进行了风洞试验，试验包括三种农业喷嘴、三种压力设置和五种风速设置。将激光雷达传感器和被动收集器（聚乙烯线）放置在喷嘴下游，以测量垂直平面内的漂移液滴。计算每条线上的漂移沉积量以及收集线相应高度处的激光雷达液滴点数，并分析这种新方法的影响因素。结果表明，三维激光雷达测量提供了丰富的空间信息，如漂移液滴分布的高度和宽度等。与被动收集器捕获的沉积量相比，三维激光雷达测量的漂移点具有较高的决定系数（>0.75），在0.2 MPa喷雾压力下的抗漂移IDK12002喷嘴的 值最大，为0.9583。用三维激光雷达进行漂移评估对空间中的液滴密度或漂移质量以及喷嘴初始液滴谱敏感；一般来说，较大的液滴密度或漂移质量以及较小的液滴尺寸不利于激光雷达检测，而合适的阈值范围仍需进一步研究。本研究表明，三维激光雷达有潜力用作快速评估喷雾漂移的替代工具。
