基于稀疏学习自适应的马铃薯联合收获机优化设计

Optimum Design of Potato Combine Harvester Based on Sparse Learning Adaptive

针对马铃薯收获机由于传动速度偏高造成的收获机阻塞和马铃薯损伤问题,对马铃薯收获机进行了优化设计,提出了一种基于稀疏自适应学习的设计方法,解决了马铃薯联合收获机输送和分级装袋流动不畅和有滞留堆积问题,提高了收获机的生产效率。为了验证马铃薯收获机优化设计后的可靠性,在不同类型的地块上对马铃薯的性能进行了测试,测试地块类型分别为平播旱地和全覆膜双垄播旱地两种。通过试验测试发现:对传动系统进行改进后,联合收获机对全覆膜双垄播旱地和平播旱地的适应性均较好,各项测试指标均比优化之前好,从而验证了传动系统优化的可靠性,对马铃薯联合收获机的改进提供了理论参考。

For the potato harvester,due to higher transmission speed caused by the harvester blocking and potato injury problems,potato harvester were designed for optimization,and it proposed a design method based on adaptive sparse learning to solve the potato harvesting machine,which is used for conveying and grading and bagging flow. The experimental place is not smooth and is retained in the accumulation of problems,which improved the production efficiency of the harvester. In order to verify potato optimization design of reliability,different types of plots the performance of potato were tested,the test plots were for flat sowing dry and fully covered double ridge sowing dry land. It was found that it improved the transmission system,combine harvester to fully covered double ridge sowing dry peace the adaptability of dryland sowing are better,the test targets than before optimization,thus validating the optimization of transmission system reliability,which provide a theoretical reference for the potato combine harvester improvement.