Design and experiment of a stereoscopic vision-based system for seeding depth consistency adjustment

IF 7.7 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Computers and Electronics in Agriculture Pub Date : 2024-08-17 DOI:10.1016/j.compag.2024.109345
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Abstract

The basic process of corn sowing includes seed selection, land preparation, fertilization, sowing, and soil compaction. Soil compaction is an important step in the sowing process, playing a crucial role in protecting the seeds, promoting germination and root development, and providing a stable growth environment for corn. Currently, mainstream soil compaction devices used in corn sowing employ non-active adjustment structures, which cannot regulate the amount of soil covering and the compaction force for individual seeds during the sowing process, making it difficult to ensure consistent sowing depth. To address these issues, this study investigates the soil compaction device on a corn planter and proposes a soil compaction device that utilizes a binocular structured light camera to detect the opening depth of the planter and flexibly adjust the soil covering and compaction force for each seed. Experimental evaluations of the device’s performance were also conducted. The design of the sowing depth consistency control system includes the selection and application of the design, motor, gearbox, binocular structured light camera, dust removal device, user interface, electric-driven soil compaction device, and control system. The experimental results showed that when the system detects a variation in trench depth of around 2 cm, the average response time of the system is 2.23 s with a standard deviation of 0.042 s. When the system detects a variation in trench depth of around 4 cm, the average response time of the system is 4.68 s with a standard deviation of 0.078 s. This suggests that the system’s response time fluctuates within 0.1 s, indicating good stability of the system. The average error of the planter’s opening depth, as measured by the binocular structured light camera, is approximately 6 mm, the success rate of detection can be maintained above 70 % under different trench depths. The dust removal device’s performance meets the requirements of the detection system. The research demonstrates that the sowing depth consistency control system developed in this study can accurately detect the planter’s opening depth during operation and adjust the soil covering, compaction force appropriately based on the depth information provided by the soil compaction device.

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基于立体视觉的播种深度一致性调整系统的设计与实验
玉米播种的基本流程包括选种、整地、施肥、播种和土壤压实。土壤压实是播种过程中的一个重要步骤,对保护种子、促进发芽和根系发育、为玉米提供稳定的生长环境起着至关重要的作用。目前,玉米播种中使用的主流土壤压实装置采用非主动调节结构,无法在播种过程中调节覆土量和单粒种子的压实力,难以保证播种深度的一致性。针对这些问题,本研究对玉米播种机上的土壤压实装置进行了研究,并提出了一种土壤压实装置,利用双目结构光摄像机检测播种机的开口深度,灵活调节每粒种子的覆土量和压实力。此外,还对该装置的性能进行了实验评估。播种深度一致性控制系统的设计包括设计、电机、变速箱、双目结构光摄像机、除尘装置、用户界面、电动土壤压实装置和控制系统的选择和应用。实验结果表明,当系统检测到沟深变化在 2 cm 左右时,系统的平均响应时间为 2.23 s,标准偏差为 0.042 s;当系统检测到沟深变化在 4 cm 左右时,系统的平均响应时间为 4.68 s,标准偏差为 0.078 s。双目结构光摄像机测量的播种机开口深度的平均误差约为 6 毫米,在不同的沟槽深度下,检测成功率可保持在 70% 以上。除尘装置的性能符合检测系统的要求。研究表明,本研究开发的播种深度一致性控制系统可在运行过程中准确检测播种机的开沟深度,并根据土壤压实装置提供的深度信息适当调整覆土、压实力。
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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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