# Axial separation simulation analysis and experiment of maize seed cylinder grading: A study on axial analysis

## TL;DR

This paper uses simulations and experiments to optimize maize seed grading by adjusting cylinder speed, angle, and feeding rate for better efficiency and accuracy.

## Contribution

The study introduces a simulation-based approach to optimize maize seed grading parameters, validated through experiments with low error margins.

## Key findings

- Cylinder speed has the highest impact on qualification rate, followed by inclination angle and feeding rate.
- The optimal grading parameters achieved a qualification rate of 93.21% and productivity of 1,033 g/s in simulation.
- Validation experiments showed a 90.15% qualification rate and 985 g/s productivity with less than 5% error from simulations.

## Abstract

This study conducted a simulation analysis of the seed grading process to address the challenges of excessive dependence on empirical parameter adjustments, low grading efficiency, and operational instability in maize cylinder grading systems. After determining the relevant characteristic parameters of maize seeds and the grading cylinder, discrete element models were established using EDEM software. The simulation investigated axial mean velocity, intra-cylinder quantity distribution, and post-sieving quantity distribution of seeds under varying cylinder speeds (14–22 r/min), inclination angles (0°–4°), and feeding rates (1,150–1,350 g/s). Orthogonal experiments and range analysis were conducted to determine the significance hierarchy of factors: for qualification rate, cylinder speed > inclination angle > feeding rate. For productivity, inclination angle > feeding rate > cylinder speed. The optimal parameter combination was cylinder speed 16 r/min, inclination angle 0°, and feeding rate 1,300 g/s. At this point, the qualification rate was 93.21%, and the productivity was 1,033 g/s. Using the optimal combination for validation experiments, the obtained qualification rate was 90.15%, and the productivity was 985 g/s. The relative errors between the experimental values and the predicted values were less than 5%, validating the simulation’s reliability and providing critical engineering implications for industrial seed grading optimization.