IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i10p1535-d923289.html
   My bibliography  Save this article

Power Consumption Influence Test of Castor Disc-Cutting Device

Author

Listed:
  • Teng Wu

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

  • Fanting Kong

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

  • Lei Shi

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

  • Qing Xie

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

  • Yongfei Sun

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

  • Changlin Chen

    (Nanjing Research Institute for Agricultural Mechanization, Ministry of Agriculture, Nanjing 210014, China)

Abstract

This study theoretically analyzed the cutting process of castor and determined the structural parameters of the key component of the castor disc-cutting device, aiming to obtain the optimal operation parameter combination and reduce the cutting resistance and power consumption during the harvesting process. The effects of the cutting-disc thickness, cutting-disc rotational speed, feeding speed, and edge angle on the cutting power consumption were studied using an orthogonal rotation combination experiment. The response surface method was used to optimize the parameters, and the mathematical relationship model between the cutting power consumption and each factor was established to determine the optimal parameter combination for disc cutting. The simulation results showed that the optimal combination of cutting parameters was cutting-disc thickness of 3 mm, cutting-disc rotational speed of 550 r/min, feeding speed of 0.6 m/s, and edge angle of 20°. Under these conditions, the cutting power consumption was 1.20375 J. The test results were basically consistent with the model prediction results. Therefore, this study provided a theoretical basis and reference for the design and improvement of castor harvesters.

Suggested Citation

  • Teng Wu & Fanting Kong & Lei Shi & Qing Xie & Yongfei Sun & Changlin Chen, 2022. "Power Consumption Influence Test of Castor Disc-Cutting Device," Agriculture, MDPI, vol. 12(10), pages 1-14, September.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:10:p:1535-:d:923289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/10/1535/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/12/10/1535/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chengjun Li & Hanshi Zhang & Qingchun Wang & Zhongjia Chen, 2022. "Influencing Factors of Cutting Force for Apple Tree Branch Pruning," Agriculture, MDPI, vol. 12(2), pages 1-10, February.
    2. Luigi Pari & Alessandro Suardi & Walter Stefanoni & Francesco Latterini & Nadia Palmieri, 2020. "Environmental and Economic Assessment of Castor Oil Supply Chain: A Case Study," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    3. Bin Zhang & Haolu Liu & Jicheng Huang & Kunpeng Tian & Cheng Shen & Xianwang Li & Xingsong Wang, 2022. "Ramie Field Distribution Model and Miss Cutting Rate Prediction Based on the Statistical Analysis," Agriculture, MDPI, vol. 12(5), pages 1-15, April.
    4. Luigi Pari & Francesco Latterini & Walter Stefanoni, 2020. "Herbaceous Oil Crops, a Review on Mechanical Harvesting State of the Art," Agriculture, MDPI, vol. 10(8), pages 1-25, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiangji Peng & Kaikai Li & Xiaoyu Wang & Guohai Zhang & Jianming Kang, 2022. "Design and Test of Stripping and Impurity Removal Device for Spring-Tooth Residual Plastic Film Collector," Agriculture, MDPI, vol. 13(1), pages 1-17, December.

    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. Walter Stefanoni & Francesco Latterini & Javier Prieto Ruiz & Simone Bergonzoli & Consuelo Attolico & Luigi Pari, 2020. "Mechanical Harvesting of Camelina: Work Productivity, Costs and Seed Loss Evaluation," Energies, MDPI, vol. 13(20), pages 1-14, October.
    2. Chris Cavalaris & Francesco Latterini & Walter Stefanoni & Christos Karamoutis & Luigi Pari & Efthymia Alexopoulou, 2022. "Monitoring Chemical-Induced Ripening of Castor ( Ricinus communis L.) by UAS-Based Remote Sensing," Agriculture, MDPI, vol. 12(2), pages 1-16, January.
    3. Walter Stefanoni & Francesco Latterini & Javier Prieto Ruiz & Simone Bergonzoli & Nadia Palmieri & Luigi Pari, 2020. "Assessing the Camelina ( Camelina sativa (L.) Crantz) Seed Harvesting Using a Combine Harvester: A Case-Study on the Assessment of Work Performance and Seed Loss," Sustainability, MDPI, vol. 13(1), pages 1-11, December.
    4. Yang Liu & Chengming Luo & Wangyuan Zong & Xiaomao Huang & Lina Ma & Guodang Lian, 2021. "Optimization of Clamping and Conveying Device for Sunflower Oil Combine Harvester Header," Agriculture, MDPI, vol. 11(9), pages 1-18, September.
    5. Luigi Pari & Efthymia Alexopoulou & Walter Stefanoni & Francesco Latterini & Chris Cavalaris & Nadia Palmieri, 2022. "The Eco-Efficiency of Castor Supply Chain: A Greek Case Study," Agriculture, MDPI, vol. 12(2), pages 1-12, February.
    6. Luigi Pari & Alessandro Suardi & Walter Stefanoni & Francesco Latterini & Nadia Palmieri, 2021. "Economic and Environmental Assessment of Two Different Rain Water Harvesting Systems for Agriculture," Sustainability, MDPI, vol. 13(7), pages 1-13, March.
    7. Dongjie Li & Shuqi Shang & Xiaoning He & Zhuang Zhao & Zengcun Chang & Yuetao Wang & Dongwei Wang, 2022. "Experiments and Analysis of a Peanut Semi-Feeding Picking Mechanism Based on the JKR Model," Agriculture, MDPI, vol. 12(9), pages 1-20, September.
    8. Moritz von Cossel, 2022. "How to Reintroduce Arable Crops after Growing Perennial Wild Plant Species Such as Common Tansy ( Tanacetum vulgare L.) for Biogas Production," Energies, MDPI, vol. 15(12), pages 1-11, June.
    9. Cervelli, Elena & Recchi, Pier Francesco & Fagnano, Massimo & Scotto di Perta, Ester & Pindozzi, Stefania, 2024. "Marginal lands between recovery and valorization. An inclusive definition to support bio-energy supply chains. The Southern Italy contexts case study," Agricultural Systems, Elsevier, vol. 217(C).
    10. Lili Shi & Bing Wang & Zhichao Hu & Hongguang Yang, 2022. "Mechanism and Experiment of Full-Feeding Tangential-Flow Picking for Peanut Harvesting," Agriculture, MDPI, vol. 12(9), pages 1-13, September.
    11. Mariusz Jerzy Stolarski, 2021. "Industrial and Bioenergy Crops for Bioeconomy Development," Agriculture, MDPI, vol. 11(9), pages 1-5, September.
    12. Luigi Pari & Alessandro Suardi & Walter Stefanoni & Francesco Latterini & Nadia Palmieri, 2020. "Environmental and Economic Assessment of Castor Oil Supply Chain: A Case Study," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    13. Walter Stefanoni & Francesco Latterini & Valantis Malkogiannidis & Vlasis Salpiggidis & Efthymia Alexopoulou & Luigi Pari, 2022. "Mechanical Harvesting of Castor Bean ( Ricinus communis L.) with a Combine Harvester Equipped with Two Different Headers: A Comparison of Working Performance," Energies, MDPI, vol. 15(9), pages 1-10, April.
    14. Junming Hou & Xu Liu & Hongjie Zhu & Zhi Ma & Ziyuan Tang & Yachen Yu & Jiuyu Jin & Wei Wang, 2023. "Design and Motion Process of Air-Sieve Castor Cleaning Device Based on Discrete Element Method," Agriculture, MDPI, vol. 13(6), pages 1-27, May.
    15. Dengyu Xiong & Mingliang Wu & Wei Xie & Haifeng Luo, 2023. "Design and Experimental Study of the Key Components of a Rape ( Brassica campestris ) Shoots (Changxiangtai 603) Flexible Clamping Harvester," Agriculture, MDPI, vol. 13(4), pages 1-20, March.
    16. Wei Xiang & Bo Yan & Yiping Duan & Zhe Tang & Lan Ma & Jiajie Liu & Jiangnan Lv, 2023. "Design and Parameter Optimization of Transverse-Feed Ramie Decorticator," Agriculture, MDPI, vol. 13(6), pages 1-16, May.
    17. Walter Stefanoni & Francesco Latterini & Luigi Pari, 2023. "Perennial Grass Species for Bioenergy Production: The State of the Art in Mechanical Harvesting," Energies, MDPI, vol. 16(5), pages 1-12, February.
    18. Daipeng Lu & Wei Wang & Encai Bao & Shilin Wang & Xue Wu & Zongchun Bai & Yuxin Tang, 2022. "Cutting Mechanical Properties of Pumpkin Grafted Seedling Investigated by Finite Element Simulation and Experiment," Agriculture, MDPI, vol. 12(9), pages 1-18, September.

    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:12:y:2022:i:10:p:1535-:d:923289. 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.