Simulation and Experimental Study on the Optimization of Operating Parameters for Coating Pellets of Agropyron Seeds

Haiyang Liu, Xuejie Ma, Zhanfeng Hou (), Liying Chen, Aijun Tan and Yishuai Liu
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Haiyang Liu: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Xuejie Ma: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Zhanfeng Hou: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Liying Chen: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Aijun Tan: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Yishuai Liu: College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China

Agriculture, 2025, vol. 15, issue 19, 1-18

Abstract: In addressing the challenges of low pelletization qualification rates, poor uniformity between seeds and powder, and difficulties in optimizing equipment parameters for agropyron seed coating, this paper integrates numerical simulation with experimental verification to optimize the working parameters of pelletization coating. The study investigates the impact of vibration frequency, vibration direction, vibration amplitude, rotational speed, and inclination angle on seed-powder mixing uniformity and single-seed pellet qualification rates through both physical experiments and simulation tests. The study found that the coefficient of variation obtained through discrete element simulation can serve as a reliable surrogate indicator for evaluating pelletization coating quality, with its variation trend highly consistent with the single-seed pellet qualification rate observed in physical experiments. A secondary regression orthogonal design experiment used these indicators to establish a second-order regression equation, thereby performing single-objective optimization of the regression model. The results showed that the relative errors between simulation and physical test parameters were 1.24% for vibration frequency, 1.08% for coating pan rotational speed, and 0.17% for coating pan inclination angle. This demonstrates the high reliability of the coefficient of variation as a surrogate indicator for pellet qualification. With the optimized parameters, the qualification rate of single-seed pellets for agropyron seeds reached 95.3%, and the relative error between model predictions and physical tests was 1.7%. These findings validate the use of the second-order regression equation for predicting and analyzing single-seed pellet qualification rates and provide valuable insights for designing small-grain forage seed pelletization coating machines and optimizing coating parameters.

Keywords: pelletization coating; numerical simulation; experimental verification; seed; optimization; coefficient of variation (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
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