Study and Testing of a Front-Blowing and Rear-Suction Enhanced Cleaning Technology for Grain Combine Harvesters

Jianning Yin, Yipeng Cui, Zehao Zha, Qiming Yu, Pengxuan Guan, Yang Wang, Xinxin Wang and Duanyang Geng ()
Additional contact information
Jianning Yin: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Yipeng Cui: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Zehao Zha: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Qiming Yu: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Pengxuan Guan: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Yang Wang: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Xinxin Wang: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China
Duanyang Geng: School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China

Agriculture, 2025, vol. 15, issue 16, 1-23

Abstract: To address the issue in high-throughput longitudinal axial-flow grain combine harvester cleaning systems, in which the extended length of the cleaning chamber results in airflow velocity attenuation and makes it difficult to efficiently and rapidly remove light impurities, a front-blowing and rear-suction enhanced cleaning technology and device was developed. Based on the investigation of the movement characteristics of the cleaning airflow within the cleaning chamber, a theoretical model was established to describe the velocity variation of the front-blowing and rear-suction enhanced cleaning airflow. CFD simulation software was employed to conduct a comparative analysis of the airflow field structure before and after improvement, aiming to identify the influence patterns of key structural parameters on the airflow field distribution. An orthogonal experiment with three factors and three levels was conducted on the improved cleaning system, focusing on the suction fan speed, vertical installation height of the suction fan, and horizontal distance between the suction fan and the sieve surface. The influence of each factor on the airflow field was analyzed, and the optimal parameter combination was obtained. When the suction fan speed was 2275 r/min, the vertical installation height was 72.5 mm, the horizontal distance to the sieve surface was 385 mm, and the airflow non-uniformity coefficient at the rear part of the screen surface was 11.17%, with a relative error of 4.39% compared to the optimization result. Finally, bench tests were conducted to verify the accuracy of the simulation results. Compared to that before improvement, the airflow non-uniformity coefficient at the rear part of the screen surface in the cleaning chamber was reduced by 59.43%, significantly improving the uniformity of airflow distribution. These findings provide both theoretical and technical support for improving the cleaning efficiency and operational performance of high-throughput grain combine harvesters.

Keywords: grain combine harvester; cleaning system; front-blowing and rear-suction; CFD simulation; airflow non-uniformity coefficient (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/16/1722/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/16/1722/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:16:p:1722-:d:1721097

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().