IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v14y2024i8p1302-d1451544.html
   My bibliography  Save this article

Study on the Bionic Design and Cutting Performance of Alfalfa Cutters Based on the Maxillary Mouthparts of Longicorn Beetles

Author

Listed:
  • Jingyi Ma

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China)

  • Kun Wu

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China
    Department of Traffic Engineering, Shandong Transport Vocational College, Weifang 261206, China)

  • Ang Gao

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China)

  • Yonghui Du

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China)

  • Yuepeng Song

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China
    Key Laboratory of Horticultural Machinery and Equipment of Shandong Province, Tai’an 271018, China)

  • Longlong Ren

    (College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai’an 271018, China
    Key Laboratory of Horticultural Machinery and Equipment of Shandong Province, Tai’an 271018, China)

Abstract

Inspired by the maxillary mouthparts of longicorn beetles, four types of bionic cutters were designed in this research to address the prevalent issues of high cutting resistance and severe stubble damage encountered during alfalfa harvesting. Finite element simulation was utilized to assess the structural integrity and cutting performance of these bionic cutters. Additionally, bench tests were conducted on a homemade stem-cutting force measurement and control rig to evaluate their effectiveness. The results indicated: (1) the bionic cutters achieved a reduction in maximum equivalent force ranging from 20.9% to 49.2% and a decrease in maximum deformation from 31.4% to 64.1% compared to conventional cutters; (2) the maximum cutting resistance of alfalfa stems was reduced by 28.6%, 43.9%, 52.4%, and 38.6%, significantly enhancing the flatness of the cut surfaces; (3) orthogonal bench tests demonstrated that the type of cutter and the slip-cutting angle significantly influenced the maximum cutting resistance of the stems ( p < 0.01), with the optimal configuration being bionic cutter c, a slip-cutting angle of 10°, and a rotational speed of 2600 rpm. In conclusion, bionic cutters demonstrate substantial advantages in reducing maximum cutting resistance and improving the flatness of alfalfa stubble, suggesting their potential for widespread application and adoption.

Suggested Citation

  • Jingyi Ma & Kun Wu & Ang Gao & Yonghui Du & Yuepeng Song & Longlong Ren, 2024. "Study on the Bionic Design and Cutting Performance of Alfalfa Cutters Based on the Maxillary Mouthparts of Longicorn Beetles," Agriculture, MDPI, vol. 14(8), pages 1-20, August.
  • Handle: RePEc:gam:jagris:v:14:y:2024:i:8:p:1302-:d:1451544
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/14/8/1302/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/14/8/1302/
    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:8:p:1302-:d:1451544. 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.