IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i3p433-d1352883.html
   My bibliography  Save this article

Research on a Vibrationally Tuned Directional Seed Supply Method Based on ADAMS-EDEM Coupling and the Optimization of System Parameters

Author

Listed:
  • Sheng Sun

    (College of Mechanical and Electronic Engineering, Shihezi University, Shihezi 832000, China
    Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery, Shihezi 832003, China)

  • Bin Hu

    (College of Mechanical and Electronic Engineering, Shihezi University, Shihezi 832000, China
    Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery, Shihezi 832003, China)

  • Xinming Wu

    (College of Mechanical and Electronic Engineering, Shihezi University, Shihezi 832000, China
    Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery, Shihezi 832003, China)

  • Xin Luo

    (College of Mechanical and Electronic Engineering, Shihezi University, Shihezi 832000, China
    Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery, Shihezi 832003, China
    Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affair, Shihezi 832003, China)

  • Jian Wang

    (Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affair, Shihezi 832003, China)

Abstract

We have combined the theory of bulk dynamics and the agronomic requirements of precision sowing with the aim of resolving the technical problems of poor seed mobility and the difficulty in controlling suction posture, which leads to an increase in the leakage rate and a reduction in seed qualification index scores. In this study, a vibrationally tuned directional seed supply method and system are proposed. We carried out a force analysis of seeds, constructed kinematic equations for seeds and seed boxes to specify the state of the seed motion, and determined the structural parameters and the range of structural parameters that affect the seed suction posture. In addition, we coupled the ADAMS-EDEM simulation of the motion process of the seed and seed boxes and analyzed the vibrational tuning process of the seeds and the angle of inclination of the bottom surface of the seed box. The speed of the eccentric wheel and the eccentric distance were used as test factors. Three-factor and three-level Box–Behnken central combination testing with a single-grain rate, multiple-grain rate, and cavity rate were used as response indicators. Mathematical models were obtained between the experimental factors and the response indicators. Multi-objective optimization of mathematical regression models was carried out with Design-Expert 10.0.4 software. The optimal parameter combination obtained was a tilt angle of 14.27°, an eccentric wheel speed of 4.48 rad/s, and an eccentricity of 1.94 mm. The rate of single grains was 90.75%, the rate of multiple grains was 3.63%, and the rate of cavities was 5.62%. In bench performance tests, using an angle of inclination of 14°, the speed of the eccentric wheel was 4.50 rad/s and the eccentricity was 2 mm. The mean value of the single-grain rate was 89.28%, the mean value of the multiple-grain rate was 3.89%, and the mean value of the cavity rate was 6.83%. The test error was within permissible limits, and reliable results were achieved for parameter optimization. The results met the technical requirements for precision sowing. The results of the study can provide academic references for theoretical research on the methodology of posturing and directional seed supply. They can also provide ideas for the design and development of seed supply systems for precision sowing machinery.

Suggested Citation

  • Sheng Sun & Bin Hu & Xinming Wu & Xin Luo & Jian Wang, 2024. "Research on a Vibrationally Tuned Directional Seed Supply Method Based on ADAMS-EDEM Coupling and the Optimization of System Parameters," Agriculture, MDPI, vol. 14(3), pages 1-19, March.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:3:p:433-:d:1352883
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/3/433/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/14/3/433/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Liu & Shijie Tian & Qingyu Wang & Huanyu Jiang, 2023. "Key Technologies of Plug Tray Seedling Transplanters in Protected Agriculture: A Review," Agriculture, MDPI, vol. 13(8), pages 1-19, July.
    2. Xinchun Ma & Qixiang Gong & Qingjie Wang & Dijuan Xu & Yinggang Zhou & Guibin Chen & Xinpeng Cao & Longbao Wang, 2022. "Design of an Air Suction Wheel-Hole Single Seed Drill for a Wheat Plot Dibbler," Agriculture, MDPI, vol. 12(10), pages 1-25, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiawei Shi & Jianping Hu & Jing Li & Wei Liu & Rencai Yue & Tengfei Zhang & Mengjiao Yao, 2024. "Design and Experiment of Planting Mechanism of Automatic Transplanter for Densely Planted Vegetables," Agriculture, MDPI, vol. 14(8), pages 1-22, August.
    2. Jinbo Ren & Chongcheng Chen & Difa Bao & Xinhui Wu & Shuhe Zheng, 2024. "Simulation Analysis and Optimization Design of Paddy Field Mud Spreader Blades for Uniform Dispersion," Agriculture, MDPI, vol. 14(3), pages 1-20, February.
    3. Abdullah Addas & Muhammad Tahir & Najma Ismat, 2023. "Enhancing Precision of Crop Farming towards Smart Cities: An Application of Artificial Intelligence," Sustainability, MDPI, vol. 16(1), pages 1-18, December.
    4. Jin Yuan & Zichen Huang, 2024. "Intelligent Agricultural Machinery and Robots: Embracing Technological Advancements for a Sustainable and Highly Efficient Agricultural Future," Agriculture, MDPI, vol. 14(12), pages 1-3, November.
    5. Zhiwei Tian & Ang Gao & Wei Ma & Huanyu Jiang & Dongping Cao & Weizi Wang & Jianping Qian & Lijia Xu, 2024. "Modeling the Mechanical Properties of Root–Substrate Interaction with a Transplanter Using Artificial Neural Networks," Agriculture, MDPI, vol. 14(5), pages 1-12, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:14:y:2024:i:3:p:433-:d:1352883. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.