利用超声波传感系统和先进的压力控制机构设计研制果园定点专用喷雾器工业样机

IF 8.9 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Arshed Ahmed , Shoaib Rashid Saleem , Muhammad Naveed Tahir , Shahram Hamza Manzoor , Qamar Zaman , Zhao Zhang , Rashed Ahmed
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引用次数: 0

摘要

可变速率技术(VRT)和定点应用是精准农业的重点研究领域之一,它能够通过自动定位植物区域来方便农民,避免不必要的农用化学品损失。定点喷洒不仅节省了昂贵的农用化学品,而且还有助于保护环境。本研究的主要目的是开发一种基于超声传感器树木检测的果园定点喷雾器(SSOS)系统。为此,将传统的两个垂直吊臂园艺喷雾器(每个吊臂上有六个喷嘴)改进为使用单个喷嘴的自动控制进行特定地点的喷洒。两个传感器吊杆安装在SSOS的两侧,位于喷雾器吊杆的前面。安装了6个超声波传感器,每个吊杆上有3个。利用功率晶体管和基于继电器的操作对所开发的喷雾器进行了快速开关电子阀的测试,测试结果表明,开关时间仅为28 ms。同样,对喷雾器进行了精确的传感器间距安装位置和传感器安装角度测试,以最大限度地减少目标树冠的漏检,测试结果表明,在实验室测试中,安装角度为0°的喷雾器效果最佳。此外,我们还开发了一种基于机器学习(ML)的决策树模型,用于压力控制机制,以保护传统喷雾器中的液压管道系统。基于规则的决策树算法通过准确预测溢出连接的切换,精确控制溢出连接(OFCs),达到94%的准确率。开发的SSOS在巴基斯坦拉瓦尔品第大学研究农场的不同柑橘果园进行了测试。试验结果表明,果园定点喷洒系统与传统喷洒系统相比,可节约38%的农药。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and development of industrial prototype of spot specific orchard sprayer using ultrasonic sensing system and advanced pressure control mechanism
Variable rate technologies (VRT) and spot-specific applications are one of the key research areas of precision agriculture with the ability to facilitate the farmers by automatically targeting only plant areas to avoid unnecessary losses of agrochemicals. Spot-specific spraying not only saves costly agrochemicals, but it can also help to protect environment. The primary objective of this study was to develop a spot specific orchard sprayer (SSOS) system based on tree detection through ultrasonic sensors. For this purpose, a traditional two vertical booms horticulture sprayer with six nozzles on each boom was modified to a spot specific spraying using automatic control of individual nozzle. Two sensor booms were installed, one on each side of the SSOS, in front of the sprayer booms. Six ultrasonic sensors were mounted, three on each boom. The developed sprayer was tested for fast switching of electronic valves using power transistors and relay-based operation, and testing results showed a switching time of only 28 ms. Similarly, the sprayer was tested for accurate sensor spacing mount position and sensor mount angle to minimize the miss detection of the target tree canopy and testing results showed that a mount angle of 0° worked best during lab testing. Furthermore, we have developed a Machine Learning (ML) based Decision Tree model for a pressure control mechanism to protect the hydraulic piping system in the traditional sprayers. The rule-based decision tree algorithm precisely controls the Overflow Connections (OFCs) through accurate predictions for switching of such connections, resulting in 94 % accuracy. The developed SSOS was tested in different citrus orchards at University Research Farms, Rawalpindi, Pakistan. The test results showed that spot specific orchard spraying system saved 38 % agrochemicals compared to traditional spraying for citrus orchards.
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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