In order to enhance the accuracy of discrete element numerical simulations in the processing of small-seed particles, it is essential to calibrate the parameters of seeds within the discrete element software. This study employs a series of physical tests to obtain the physical and contact parameters of red clover seeds. A discrete element model of red clover seeds is established. Plackett–Burman Design, steepest ascent, and Central Composite Design experiments are sequentially conducted. The simulation deviation of the resting angle of red clover seeds is employed as the evaluation criterion for parameter optimization. The results indicate that the coefficients of static friction between red clover seeds, the coefficients of rolling friction between red clover seeds, and the coefficients of static friction between red clover seeds and the steel plates significantly influence the resting angle. Modeling was performed using a backpropagation neural network, a genetic algorithm–optimized BP network, particle swarm optimization, and simulated annealing. It was found that GA-BP ensured both accuracy and stability. Compared to the traditional response surface methodology, GA-BP showed better fitting performance. For the optimized red clover seed simulation, the error between the angle of repose and the physical experiment was 0.98%. This research provides new insights into the calibration of small-grain seed parameters, demonstrating the value of GA-BP for precision modeling.

Regarding the issue of low granulation qualification rates during the granulation coating of red clover seeds, this study theoretically analyzed the force conditions of seeds and powder particles under the action of liquid to obtain the main factors affecting seed coating quality. During the seed granulation coating process, an intermittent powder supply method combined with continuous liquid supply was utilized to control the ratio of powder to liquid. Using the granulation qualification rate as the evaluation index, single-factor experiments were conducted to investigate the effects of coating pan fill ratio, single powder supply amount, powder supply interval, and liquid supply amount on the quality of red clover seed granulation coating. Based on the results of the single-factor experiments, orthogonal experiments were conducted, revealing that the interaction of factors would influence the experimental results. To further optimize the quality of seed granulation coating, the mechanisms of powder and liquid in the adhesion process on granulation coating were explored. Orthogonal experiments were conducted on the process parameters of the granulation coating machine, and the GA-BP model was employed for optimization and solution. The optimal process parameter combination obtained was a coating pan fill ratio of 33.78 %, a single powder supply amount of 5.17 g, a powder supply interval of 7.7 s, and a liquid supply amount of 0.42 mL/s. Under this optimal parameter combination, granulation coating experiments with red clover seeds were performed, and the seed granulation coating quality was relatively high, with a granulation qualification rate of 97.7 %. The research results can provide a reference for optimization experiments on coating irregular seeds.

In order to solve the problem of the low qualification rate of the pilling and coating of small-grain forage seeds, a vibration force field is introduced to the traditional vertical disk coating machine to promote the mixing of materials and improve the qualification rate of the pilling. Using the typical small-grain forage seed red clover as an example, we used the vibration force field after adding seed powder particles to a coating pot for the theoretical analysis of the force situation, using the discrete element software EDEM to construct a red clover seed simulation model with the coefficient of discretization as the evaluation index. We studied the effects of the rotational speed of the coating pot, the vibration frequency of the pot, the amplitude of the vibration of the pot, and the other operating parameters of the pot on the uniformity of the seed powder mixing, with the pelletization of the pass rate as the physical evaluation standard, using a one-way test to study the effect of operating parameters on the pelletization pass rate. We used the qualified rate as the physical evaluation standard, through a single-factor test, to study the influence of the working parameters on the qualification rate of the pilling. The results show that the simulation test evaluation index of the discrete coefficient and the physical test evaluation index of the pilling qualification rate with the change rule of the working parameters is consistent with the discrete coefficient, and can be used as an indirect evaluation index of the quality of pilling. To further determine the optimal combination of working parameters, a quadratic regression orthogonal design test was conducted with the discrete coefficients as the evaluation index, and the second-order regression equations of the red clover seeds were established and analyzed by ANOVA using Design-Expert software. The study shows that, when the rotational speed of the coating pot is 307.204 rpm, the vibration frequency is 2.526 Hz, and the vibration amplitude of the coating pot is 5.843 mm, the predicted coefficient of dispersion at this time is 8.1%. Simulation using the best combination of parameters to obtain the average value of the dispersion coefficient of 8.4%, relative to the predicted value of 3.7%, indicated that the optimization of the experimental regression model is accurate, and the results obtained for the vibration of small seeds under the conditions of the design of the pellet granulation coating machine and the optimization of the pelletization coating process parameters have a certain degree of reference significance.

Paddy field leveling is an essential step before rice transplanting. During the operation of a paddy field grader, a common issue is the wrapping of rice straw around the blades, resulting in a low rice straw burial rate. This study focused on analyzing the operating parameters of a disc spring–tooth-combined paddy field grader. A soil–straw mechanism simulation model was created using EDEM 2021 software to simulate the field operation status. Firstly, the single-factor test was carried out, with the working speed, the working depth of the disc cutter roller, and the rotation speed of the cutter roller as the factors and the straw-buried rate (SBR) and the machine forward resistance (MFR) as the test indexes, and the parameter range was optimized. The parameters were optimized by the response surface method (RSM) and machine learning algorithms. The results indicated that the genetic algorithm–back propagation (GA-BP) neural network outperformed other optimization models in terms of prediction accuracy and stability. By utilizing the GA-BP regression model and RSM model for regression fitting, two sets of optimal parameter combinations were obtained. Verification experiments were carried out using two sets of parameter combinations. Taking the average of the experimental results, the simulation results showed that the straw burial rate was 93.47% and the forward resistance was 6487 N for the parameter combinations of RSM, and the straw burial rate was 94.86% and the forward resistance was 6352 N for the parameter combinations of GA-BP; the field experiments showed that the straw burial rate was 92.86% and the forward resistance was 6518 N for the parameter combinations of RSM, and the straw burial rate was 95.17% and the forward resistance was 6249 N for the parameter combinations of GA-BP. The results demonstrated that the GA-BP prediction model exhibited better predictive capabilities compared to the traditional RSM, providing more accurate predictions of the paddy field grader’s field operation performance.

The calibration of the powder simulation parameters could improve the accuracy of the pelletizing and coating simulation process. In this paper, we take coated powder (after this referred to as powder) as the research object, based on particle amplification theory, combined with physical tests to calibrate the contact parameters of powder and seeds (after this referred to as seeds), conduct the angle of repose simulation tests of powder, carry out Plackett-Burman test, steepest climb test, and Box-Behnken test in turn, and establish quadratic regression equation to obtain the best combination of powder simulation parameters. The difference between the contact parameter combinations obtained from the simulation tests and the physical test results is less than 1%, providing some reference for calibrating similar powder material parameters.