基于遗传算法的水稻整株秸秆还田埋草弯刀的设计与试验

    Design and test on straw-mulching cutlass of whole rice straw returning machine based on genetic algorithm

    • 摘要: 遗传算法是模拟生命进化机制的搜索和优化方法,它的全局最优和隐含并行性适应求解复杂的优化问题。该文以水稻整株秸秆还田机的主要工作部件——埋草弯刀为研究对象,对其进行受力分析,建立了以刀片组合参数为设计变量的功耗优化模型,提出了基于遗传算法的弯刀优化方法,优化得到刀片最小功耗为5.12 kW。进行验证试验,得出最优参数组合下的功耗最小为5.5305 kW。试验数据与优化结果相吻合,证明优化方法可行,可以为整机优化提供理论 参考。

       

      Abstract: Genetic algorithm is a kind of search and optimization method which based on the life-evolution mechanism, and it can be used to solve complex optimization problems for its peculiarity of the global optimum and the implied parallel. This paper took straw-mulching cutlass as study object which was the main working part of the whole rice straw returning machine, and its force analysis was carried out. The optimization model of power loss was established by taking cutter slices combination parameters as design variable, and the optimization method based on genetic algorithm was developed. Results showed that the minimum power loss of cutter slices was 5.12 kW. The validation experiments verified that the minimum power loss was 5.5305 kW under the conditions of optimum parameter combination, which accorded with optimization results. The optimization method is feasible, which can provide theoretical reference for the whole machine optimization.

       

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