基于BTO多目标遗传算法的播种机性能优化设计

受播种地形和地域的影响,大部分播种机的播种质量、播种效率和能耗不能发挥到最佳状态,为了提高播种机的作业性能,深入挖掘了按顾客订单生产(Build-to-Order,BTO)模式的一般性意义,并将该模式引入到了播种机的优化设计中,提出了一种基于BTO模式的多目标速度控制遗传算法优化模型。根据播种质量、效率和能耗的要求,首先确定了BTO模式下播种机性能优化的初始参数,利用多目标函数确定了播种机的速度控制模型,并利用遗传算法进行了优化设计。最后,通过试验样机对播种机的播种性能进行了测试,结果表明:使用多目标遗传算法对播种机的性能进行优化后,播种机的播种质量、播种效率和播种能耗有了明显的改善,为新型播种机的研发提供了较有价值的参考。

Performance Optimization Design for the Feeder Based on BTO multi-objective Genetic Algorithm

Affected by the terrain and geographical sowing , most of the seeder can not play to the best state for sowing quality , the seeding efficiency and the energy consumption .In order to improve the operating performance of the seeder , the study in-depth excavation of the according to the general meaning of customer orders to production ( Build-to-Order, the BTO) , and the model is introduced into the optimization design of seeder in is proposed based on BTO mode of multi target speed control genetic algorithm optimization model .According to requirements of the sowing quality , efficiency and energy consumption , first it determines the BTO seeder performance optimization of initial parameters by using multi -ob-jective function to determine the speed control model of the seeding machine .And it uses genetic algorithm to the optimi-zation design .Finally , it tests the experimental prototype of the seeder seeding performance .The test results show that by using multi-objective genetic algorithm of the seeder performance after optimization , it has significantly improved sowing quality , sowing and planting efficiency and energy consumption , which provides a valuable reference data for the research and development of novel sowing machine .