IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i6p822-d1401515.html
   My bibliography  Save this article

Performance Optimization and Experimental Study of Small-Scale Potato-Grading Device

Author

Listed:
  • Haohao Zhao

    (College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Weigang Deng

    (College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Shengshi Xie

    (College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

  • Zexin Zhao

    (College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China)

Abstract

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices.

Suggested Citation

  • Haohao Zhao & Weigang Deng & Shengshi Xie & Zexin Zhao, 2024. "Performance Optimization and Experimental Study of Small-Scale Potato-Grading Device," Agriculture, MDPI, vol. 14(6), pages 1-16, May.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:6:p:822-:d:1401515
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/6/822/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/6/822/
    Download Restriction: no
    ---><---

    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:6:p:822-:d:1401515. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.