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仿生香蕉秸秆粉碎装置关键部件作业参数优化与试验

Optimization and experiment of operating parameters of key components of bionic banana straw crushing devices

  • 摘要: 目前用于香蕉秸秆粉碎的刀具在使用过程中存在刀具磨损量大、刀具易断裂、刀具适应性差等问题。结合香蕉秸秆含水量高、纤维含量丰富等物理特性,基于仿生学原理,通过狼爪获取灵感,获取仿狼爪轮廓曲线刀刃曲线方程,加工出一种仿生式减阻型秸秆粉碎刀,并设计香蕉秸秆粉碎刀轴。运用中心组合试验设计理论对秸秆还田机作业关键参数还田机前进速度、刀轴转速、刀片厚度进行研究,采用二次正交旋转组合设计试验方法并用Design-Expert进行数据处理,建立秸秆粉碎合格率的回归数学模型并进行方差分析。分析得出影响秸秆粉碎合格率的显著性顺序由大到小为刀轴转速、刀片厚度、还田机前进速度。通过响应曲面法得出最优作业参数组合为:还田机前进速度为4.72 km/h、刀轴转速为1 626.67 r/min、刀片厚度为9.84 mm,此时,香蕉秸秆粉碎合格率为97.28%。在最优参数组合的情况下,实际秸秆粉碎合格率为96.94%。通过与直型粉碎刀进行对比试验,秸秆粉碎合格率提高2.34个百分点。该研究为提高香蕉秸秆粉碎还田机作业质量提供参考。

     

    Abstract: At present, there are problems in the process of banana straw crushing, such as extensive tool wear, tool breakage, and poor tool adaptability during use. This paper combined the physical characteristics of banana straw with high water content and rich fiber content. Based on the principle of bionics, this paper was inspired by wolf claws to obtain the curve equation of the contour curve of the imitated wolf claws and process a bionic drag reduction straw crushing knife. The banana straw crushing cutter shaft was designed. The forward speed of the returning machine, the rotation speed of the cutter shaft, and the thickness of the blade were studied by using the central combination test design theory. Design-Expert conducted data processing and established a mathematical regression model of the qualified rate of straw crushing and performed variance analysis. The analysis showed that the significant sequence that affects the qualified rate of straw crushing was the rotation speed of the cutter shaft, the thickness of the blade, and the forward speed of the returning machine from large to small. The optimal combination of operating parameters obtained by the response surface method was: the forward speed of the returning machine at 4.72 km/h, the rotation speed of the cutter shaft at 1 626.67 r/min, and the blade thickness at 9.84 mm. At this time, the qualified rate of straw crushing was 97.28%. In the case of the optimal parameter combination, the actual qualified rate of straw crushing was 96.94%. Through a comparative test with a straight crushing knife, it was concluded that the straw crushing qualification rate had increased by 2.34%. This research provided a reference for improving the operational quality of banana straw crushing machines.

     

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