Author
Listed:
- Peiyu Wang
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
- Huting Wang
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
- Ruoyu Zhang
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
- Rong Hu
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
- Beibei Hao
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
- Jie Huang
(College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China
Key Laboratory of Modern Agricultural Machinery Corps, Shihezi 832003, China)
Abstract
Cotton processing is the process of converting harvested seed cotton into lint by cleaning, ginning, and cleaning the lint. The real-time acquisition of lint parameters during processing is critical in improving cotton processing quality and efficiency. The existing online inspection system cannot realize quantitative sampling detection, resulting in large fluctuations in the detection of moisture rate, and the impurity content of lint can only be measured according to the number of impurity grains and the percentage of impurity areas. This research developed a quantitative sampling device for cotton lint processing that can collect the right number of cotton samples and obtain the weight of the samples, laying the foundation for the accurate detection of cotton lint dampness and impurity rates. This research aimed to develop an online quantitative sampling device with a sampling plate as its core. The quantitative sampling procedure, consisting of a gas–solid two-phase flow in a cotton pipeline, was numerically simulated and experimentally analyzed using computational fluid dynamics (CFD) and the discrete element method (DEM). According to the coupling results, the maximum pressure differential between the top and bottom regions of the sampling plate when conveying was 1024.45 Pa. This pressure is adequate to allow for cotton samples to accumulate on the sampling plate. Simultaneously, the steady conveying speed of lint is 59.31% of the unloaded conveying wind speed, providing a theoretical foundation for the sampling time of the quantitative sample device in the processing chain. The results from testing the prototype indicate that the quantitative sampling device in the cotton flow can effectively perform the quantitative sampling of cotton lint under uniform conditions, with a sampling pass rate of 84%.
Suggested Citation
Peiyu Wang & Huting Wang & Ruoyu Zhang & Rong Hu & Beibei Hao & Jie Huang, 2024.
"Numerical Simulation of an Online Cotton Lint Sampling Device Using Coupled CFD–DEM Analysis,"
Agriculture, MDPI, vol. 14(1), pages 1-18, January.
Handle:
RePEc:gam:jagris:v:14:y:2024:i:1:p:127-:d:1319733
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