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Optimization of the Process Parameters of an Air-Screen Cleaning System for Frozen Corn Based on the Response Surface Method

Author

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  • Ning Zhang

    (Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
    College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China)

  • Jun Fu

    (Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
    College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
    Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China)

  • Zhi Chen

    (College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
    Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China)

  • Xuegeng Chen

    (College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832000, China)

  • Luquan Ren

    (Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
    College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China)

Abstract

The threshing of frozen corn is accompanied by breakage and adherence, which influence the cleaning performance when the corn-cleaning mixture is separated and cleaned. In order to reduce the impurity ratio and loss ratio during frozen corn cleaning and provide theoretical support for frozen corn combine harvesting, this study employed a self-made air-screen cleaning system with adjustable parameters. The optimal process parameters of frozen corn cleaning were determined by using the response surface method (RSM). The influences of the fan speed (FS), vibrational frequency (VF), and screen opening (SO) on the cleaning performance were explored. The results showed that all three process parameters had significant effects on the impurity ratio (IR) and loss ratio (LR). The fan speed had the most significant impact. The cleaning performance was optimal when the fan speed was 102.7 rad/s, the vibration frequency was 6.42 Hz, and the screen opening was 21.9 mm, corresponding to a 0.80% impurity ratio and a 0.61% loss ratio. The predicted values of the regression models were consistent with the experimental results with a relative error of less than 5%. The reliability and accuracy of regression models were established and confirmed.

Suggested Citation

  • Ning Zhang & Jun Fu & Zhi Chen & Xuegeng Chen & Luquan Ren, 2021. "Optimization of the Process Parameters of an Air-Screen Cleaning System for Frozen Corn Based on the Response Surface Method," Agriculture, MDPI, vol. 11(8), pages 1-18, August.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:8:p:794-:d:617870
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    References listed on IDEAS

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    1. Chen, Shuai & Gong, Binlei, 2021. "Response and adaptation of agriculture to climate change: Evidence from China," Journal of Development Economics, Elsevier, vol. 148(C).
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    Cited by:

    1. Jun Wu & Qing Tang & Senlin Mu & Lan Jiang & Zhichao Hu, 2022. "Test and Optimization of Oilseed Rape ( Brassica napus L.) Threshing Device Based on DEM," Agriculture, MDPI, vol. 12(10), pages 1-21, September.

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