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Design and Parameters Optimization of Key Components of Seed Peanut Shelling Test Bench Based on Cohesive Model

Author

Listed:
  • Chengtao Xu

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Awei Zhu

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

  • Yanfen Liu

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
    Collaborative Innovation Center for Shandong’s Main Crop Production Equipment and Mechanization, Qingdao 266109, China)

  • Shuqi Shang

    (College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China)

Abstract

In order to improve the shelling efficiency of peanuts, the fracture mechanism of peanuts and the key components of the shelling test bench were studied. Firstly, the finite element method based on the cohesive element model was used to analyze the crack propagation of peanuts; the energy required for peanuts to crack was 0.06 J, and the maximum loading force was 30 N. Combined with the physical properties, mechanical properties, and shell-breaking energy of peanuts, the parameters of the two key components of the shell-breaking device and the adjustable grinding device were designed. The loading angle of the shell-breaking device was 30°, the mass of the rod was 1.5 kg, the mass of the hammer was 0.1 kg, the total length was 0.25 m, and the external contour of the grinding device was triangular. Through the field experiment, the single-factor test and the three-factor three-level regression test were designed, respectively, and the regression model of the removal rate and the damage rate was established. According to the response surface analysis of the regression model, when the feeding quantity is 12 pods/s, the speed of gear is 250 revolutions per minute, and the shelling clearance is 9.23 mm; the peanut removal rate reached 95.61%, and the kernel damage rate was 5.41%. However, the feeding amount was low and the damage rate was high, which could provide a reference for the future seed peanut sheller.

Suggested Citation

  • Chengtao Xu & Awei Zhu & Yanfen Liu & Shuqi Shang, 2024. "Design and Parameters Optimization of Key Components of Seed Peanut Shelling Test Bench Based on Cohesive Model," Agriculture, MDPI, vol. 14(12), pages 1-21, December.
    • Handle: RePEc:gam:jagris:v:14:y:2024:i:12:p:2248-:d:1539072
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    References listed on IDEAS

    as
    1. Xuan Liao & Huanxiong Xie & Zhichao Hu & Jiannan Wang & Minji Liu & Jiyou An & Hai Wei & Huijuan Zhang, 2024. "Peanut-Shelling Technologies and Equipment: A Review of Recent Developments," Agriculture, MDPI, vol. 14(7), pages 1-26, July.
    2. Hongbo Du & Nan Lu & Chuanrong Li, 2023. "Study on Revealing Peanut-Related Disease Prevention Gene Clusters via Whole Transcriptome Sequencing," Agriculture, MDPI, vol. 13(8), pages 1-16, August.
    3. Lili Yang & Changlong Wang & Jianfeng Yu & Nan Xu & Dongwei Wang, 2023. "Method of Peanut Pod Quality Detection Based on Improved ResNet," Agriculture, MDPI, vol. 13(7), pages 1-20, July.
    4. Mohammad Askari & Yousef Abbaspour-Gilandeh & Ebrahim Taghinezhad & Ahmed Mohamed El Shal & Rashad Hegazy & Mahmoud Okasha, 2021. "Applying the Response Surface Methodology (RSM) Approach to Predict the Tractive Performance of an Agricultural Tractor during Semi-Deep Tillage," Agriculture, MDPI, vol. 11(11), pages 1-14, October.
    5. Zhen Tan & Fengzhen Liu & Yongshan Wan & Suqing Zhu & Jing Zhang & Kun Zhang & Lu Luo, 2023. "Morphological and Physiological Mechanism of Activating Insoluble Inorganic Phosphorus of Different Peanut ( Arachis hypogaea L.) Varieties under Low Phosphorus," Agriculture, MDPI, vol. 13(12), pages 1-14, December.
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