使用GA-BP神经网络优化Trifolium pratense L种子颗粒涂层的工艺参数
Xuejie Ma1, Min Liu2, Zhanfeng Hou1,3
1College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China.
Heliyon
|September 27, 2024
概括
优化红三叶草种子颗粒涂层显著提高了质量. 研究人员确定了关键因素和最佳参数,实现了增强种子涂层的97.7%粒度合格率.
科学领域:
- 农业工程 农业工程
- 材料科学 材料科学 材料科学
背景情况:
- 红三叶草种子涂层的低颗粒素合格率是一个挑战.
- 了解影响种子和粉末颗粒的力量对于改善涂层质量至关重要.
研究的目的:
- 分析影响红三叶草种子颗粒涂层质量的因素.
- 为了优化不规则种子的颗粒涂层过程.
主要方法:
- 在涂层过程中对力量的理论分析.
- 单因素和直角实验用于评估过程参数.
- 应用GA-BP模型进行参数优化.
主要成果:
- 确定了涂料填充率,粉末供应,粉末间隔和液体供应作为关键因素.
- 确定最佳参数:33.78%的填充比率,5.17g粉末,7.7秒间隔,0.42mL/s液体.
- 在最佳条件下实现了97.7%的颗粒素合格率.
结论:
- 这项研究为红三叶草种子颗粒涂层提供了一个优化的工艺.
- 这些发现为有效地涂覆不规则种子提供了宝贵的见解.
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