基于改进遗传算法的秸秆还田机刀片功耗优化

为降低秸秆还田机的功耗，以秸秆还田机的刀片为研究对象，对刀片的结构和运动参数进行优化.首先通过分析刀片受力情况建立刀片功耗数学模型，并通过田间试验验证模型的正确性;其次对遗传算法进行改进，使用权威测试函数验证改进后算法的可行性与优越性;最后使用改进遗传算法对刀片功耗数学模型进行优化，并利用ANSYS Workbench平台对优化前后的刀片进行结构静力学分析.优化结果表明刀片的功耗值由优化前的19.3kW下降到18.06kW，降低了6.4%，结构静力学分析结果表明刀片优化后结构的合理性和可行性.

Blade Power Consumption Optimization of Straw Crushing Machines Using the Improved Genetic Algorithm

To reduce the power consumption of straw crushing machines， the blade of straw crushing machines was taken as the research object to optimize its structure and motion parameters. A mathematical model of blade power consumption was established by analyzing the blade force， and the correctness of the model was verified by field experiments. An advanced genetic algorithm was proposed， and its feasibility and superiority were verified by using standard test functions. The mathematical model was optimized by using the advanced genetic algorithm， and the structural static analysis of the blades before and after optimization was carried out by using the ANSYS Workbench platform. The optimization results showed that the power consumption is reduced by 6.4% compared with that before optimization， from 19.3kW to 18.06kW. The results of structural static analysis showed that the optimized structure is reasonable and feasible.