农业机械学报2025，Vol.56Issue(9)：482-491,10.DOI:10.6041/j.issn.1000-1298.2025.09.039
苹果树冠层仿形对靶施药控制系统设计与试验
Design and Experiment of Apple Tree Canopy Profiling Targeted Spraying Control System
摘要
Abstract
Aiming to address the issues of low pesticide utilization efficiency and poor spray uniformity in traditional orchard spraying operations,a rocker-arm profiling targeted spraying control system was developed for apple tree canopies in conventional orchards in Xinjiang.The system employed multi-channel ultrasonic sensor arrays to capture canopy contour data,integrated with adaptive Kalman filtering to reduce measurement errors and map canopy boundaries accurately.A positional PID closed-loop control algorithm dynamically adjusted the profiling arm to envelop the canopy precisely.Field trials in Manas County demonstrated maximum positioning deviations of 32 mm,41 mm,and 48 mum at distances of 0.6 m,0.8m,and 1.0 m from the canopy,respectively,with maximum deviation rates not exceeding 5.33％.Validation tests for the profiling targeted spraying control system on apple tree canopies were conducted by using quantitative metrics,including average droplet density,average droplet deposition volume,pesticide adhesion rate,and spraying coefficient of variation(C V).Results demonstrated that profiling targeted spraying achieved 72.4 droplets/cm2(average droplet density),2.03 μL/cm2(deposition volume),49.8％adhesion rate,and 26.4％CV.Compared with fixed-distance targeted spraying,profiling spraying improved droplet density by 64.2％,deposition volume by 40％,and adhesion rate by 29.7％,while reducing CV by 42.5％,enhancing pesticide utilization efficiency and spraying uniformity.关键词
苹果树冠层/自动仿形/精准施药/自适应卡尔曼滤波算法/位置式PID算法Key words
canopy layer of apple trees/automatic profiling/precision application of pesticides/adaptive Kalman filtering algorithm/positional PID control algorithm分类
农业科技引用本文复制引用
谭玉磊,张景,陈金成,潘峰,纪超,赵岩..苹果树冠层仿形对靶施药控制系统设计与试验[J].农业机械学报,2025,56(9):482-491,10.基金项目
兵团科技合作计划项目(2022BC007)、兵团科技创新人才计划项目(2021CB035)、兵团英才支持计划青年项目和石河子大学国际科技合作推进计划项目(GJHZ202404) （2022BC007）
