{"title":"Design and experiment of a stereoscopic vision-based system for seeding depth consistency adjustment","authors":"","doi":"10.1016/j.compag.2024.109345","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":50627,"journal":{"name":"Computers and Electronics in Agriculture","volume":null,"pages":null},"PeriodicalIF":7.7000,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Electronics in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168169924007361","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
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.
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.