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Investigation into Experimental and DEM Simulation of Guide Blade Optimum Arrangement in Multi-Rotor Combine Harvesters

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  • Zhenwei Liang

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Jun Li

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Jianmin Liang

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Yifan Shao

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Tengfei Zhou

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Zengyong Si

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

  • Yaoming Li

    (Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China)

Abstract

The cleaning performance of the cleaning shoe of a multi-rotor combine harvester has proven to be poor owing to the threshed output entering the cleaning section in an uneven manner. Experimental results indicated that the arrangement of the guide blades on the return plate surface has a significant effect on the threshed output distribution. In this paper, DEM (discrete element method) simulations were carried out in the EDEM software to examine the effect of the height of the guide blade, the installation angle, and the number of guide blades on threshed output distribution before entering the cleaning shoe. Based on the simulated results under different guide blades arrangements, the optimum arrangement location was obtained. The simulation’s results were verified by a field experiment and were consistent with the experimental results. The field experiment results indicate that the cleaning performance significantly improved with the proper guide blade arrangement. The corresponding grain impurity ratio declined significantly from 1.26% to 0.67%, and the grain sieve loss ratio, with a decrease of 53.2%, was reduced from 1.11% to 0.52%.

Suggested Citation

  • Zhenwei Liang & Jun Li & Jianmin Liang & Yifan Shao & Tengfei Zhou & Zengyong Si & Yaoming Li, 2022. "Investigation into Experimental and DEM Simulation of Guide Blade Optimum Arrangement in Multi-Rotor Combine Harvesters," Agriculture, MDPI, vol. 12(3), pages 1-14, March.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:3:p:435-:d:775868
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    Cited by:

    1. Dianlei Han & Congxu Wang & He Zhang & Hao Pang & Xinzhong Wang & Xuegeng Chen & Xiangyu Wen, 2025. "Advances in Mechanized Harvesting Technologies and Equipment for Chili Peppers," Agriculture, MDPI, vol. 15(11), pages 1-34, May.
    2. Weijian Liu & Xiwen Luo & Shan Zeng & Li Zeng & Zhiqiang Wen, 2022. "The Design and Test of the Chassis of a Triangular Crawler-Type Ratooning Rice Harvester," Agriculture, MDPI, vol. 12(6), pages 1-17, June.
    3. Jianpeng Jing & Hongyan Sun & Runzhi Liang & Shuren Chen & Zhong Tang & Xiaoying He & Yuxuan Chen, 2025. "Noise Testing of the Conveyor Trough Sprocket and Surface Noise Reduction Performance Evaluation of the Cavity Structure in a Combine Harvester," Agriculture, MDPI, vol. 15(12), pages 1-23, June.
    4. Sheng Tai & Zhong Tang & Bin Li & Shiguo Wang & Xiaohu Guo, 2025. "Cumin-Harvesting Mechanization of the Xinjiang Cotton–Cumin Intercropping System: Review of the Problem Status and Solutions," Agriculture, MDPI, vol. 15(8), pages 1-24, April.
    5. Yuxuan Chen & Shiguo Wang & Bin Li & Yang Liu & Zhong Tang & Xiaoying He & Jianpeng Jing & Weiwei Zhou, 2025. "Influence Mechanism and Optimal Design of Flexible Spring-Tooth Reel Mechanism for Soybean Pod-Shattering Reduction," Agriculture, MDPI, vol. 15(13), pages 1-22, June.
    6. Sheng Tai & Zhong Tang & Bin Li & Shiguo Wang & Xiaohu Guo, 2025. "Intelligent Recognition and Automated Production of Chili Peppers: A Review Addressing Varietal Diversity and Technological Requirements," Agriculture, MDPI, vol. 15(11), pages 1-26, May.

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