水稻硬质育秧盘全自动起盘机提升与叠盘装置研究

Lifting and Stacking Device of Automatic Tray Lifting Machine for Rice Hard Tray Seedling

摘要:

针对现有叠盘暗室育秧模式下全自动起盘机存在起盘合格率和工作稳定性下降，输送阶段易造成秧苗、秧盘损伤等问题，改进设计一种具有轴向辅助推送秧盘功能的钩杆式提升装置，并构建仿真试验平台确定影响其工作性能的主要参数及取值范围；确定关键部件循环叠盘装置的结构参数，建立多情形目标评价结果函数，并通过Matlab插值法对评价指标进行标准化；采用二次旋转正交组合试验，以托盘间距、横向输送速度、抬起角为试验因素，起盘合格率、叶损伤率、硬盘损伤率和伤秧数为性能评价指标，对试验结果进行响应曲面分析、回归分析。应用Design-Expert 11进行多目标参数组合优化。在托盘间距为190mm、横向输送速度为0.20m/s、抬起角为72°的条件下，田间验证试验得到起盘合格率为97.5%，叶损伤率为0.52%，硬盘损伤率0.45%，伤秧数为9，与理论优化值误差小于1%，比优化前合格率提升5.6个百分点，叶损伤率降低3.5个百分点，减少秧苗损伤，硬盘损伤率降低3.8个百分点。

Abstract:

The existing darkroom mode of the automatic tray winch has encountered problems such as a decline in qualification rate and working stability, as well as damage to seedlings and rice trays during transportation. To address these issues, an improved hook rod lifting device with axial auxiliary push function for rice trays was designed. A simulation single factor test platform was constructed to determine the main parameters and their value range that affected its performance. The structure parameters of key components were determined, and a multi-case target evaluation result function was established by using Matlab interpolation method for standardization of evaluation index. The quadratic regression orthogonal rotating center combination test method was adopted, with tray spacing, transverse conveying speed, and lifting angle as test factors, while tray lifting qualification rate, leaf damage rate, hard disk damage rate, and number of injured seedlings served as performance evaluation indexes. Parameter combination optimization tests were conducted on the Rocky-DEM simulation test platform that had been constructed. Design-Expert 11 software was used for multi-objective parameter combination optimization. Field verification tests under conditions of 190mm tray spacing, 0.20m/s transverse conveying speed, and 72° lifting angle achieved a tray lifting qualification rate of 97.5%, leaf damage rate of 0.52%, hard disk damage rate of 0.45%, number of injured seedlings at 9 units, with an error of less than 1% compared with the theoretically optimized value. In comparison with the non-optimized lifting and stacking device, the pass rate for tray lifting was increased by 5.6 percentage points, leaf damage rate was decreased by 3.5 percentage points, reducing seedling damage, and hard tray damage rate was decreased by 3.8 percentage points.