农业机械学报2017，Vol.48Issue(9)：70-75,6.DOI:10.6041/j.issn.1000-1298.2017.09.009
摆动式间苗机器人锄刀优化设计与试验
Optimal Design and Experiment of Thinning Hoe for Swing Motion Thinning Robot
摘要
Abstract
As the scale of agricultural production gradually expands,agriculture is developing forward to mechanization and intelligent direction.At present the main ways of domestic thinning are artificial thinning and chemical control thinning.Artificial thinning has the disadvantages of low efficiency and high labor intensity.Chemical control thinning makes seedling emergence come out not evenly,and people have to fill the gaps manually.Mechanical thinning can improve the working efficiency and bring great economic benefits with even seedling.The swing motion thinning robot was designed for the first thinning of seedlings and the kinematics model was established for the optimal to simulate the moving path.Then the virtual orthogonal experiment was done by different optimal edge lengths,different angles between optimal edge and optimal handle,different optimal handle lengths and different distances between optimal handle and center of crop-row.The prediction model of weeding rate and wounded seedling rate were analyzed by taking the coverage rate and the inbreaking rate as evaluation indexes.Based on the calculation,the best parameters in combination were as follows:distance between optimal handle and center of crop-row of 55 mm,optimal edge length of 75 mm,optimal handle length of 130 mm,angle between optimal edge and optimal handle of 65°.The experiment result verified that the simulation and orthogonal experiment were accurate and efficient with good operation effectiveness of the prototype,and the weeding rate reached 89.4％,yet the wounded seedling rate was only 7.2％.关键词
间苗机器人/机械间苗/间苗锄刀/参数优化/正交试验Key words
thinning robot/mechanical thinning/thinning hoe/parameter optimization/orthogonal experiment分类
农业科技引用本文复制引用
孙哲,张春龙,马瑶瑶,张淦,李伟,谭豫之..摆动式间苗机器人锄刀优化设计与试验[J].农业机械学报,2017,48(9):70-75,6.基金项目
“十二五”国家科技支撑计划项目(2015BAD23B02)和国家自然科学基金项目(31601217) （2015BAD23B02）
