摘要
喷杆-吊杆组合式喷雾机被广泛应用于棉花催熟脱叶剂的喷施,由于棉花采用密植栽培模式,棉花冠层中下部脱叶剂喷施覆盖率低,脱叶效果差,严重影响了机采棉品质。为提高棉花中下部的喷洒覆盖率,减小喷雾机行驶阻力,提出吊杆分禾器参数优化方案,采用Box-Behnken设计制定试验方案,以分禾器前倾角、安装高度、作业速度等参数作为试验因素,通过田间试验获取雾滴覆盖率、分禾阻力等响应数据,使用椭球基神经网络(Ellipsoidal basis function neural network,EBFNN)逼近响应和试验因素之间的关系,建立精度可靠的近似模型,基于该模型对试验因素分析、优化。并得到最佳试验参数组合:分禾器离地高度210 mm、分禾器前倾角12°、喷雾机作业速度4 km/h。在此条件下进行田间试验,棉花冠层平均雾滴覆盖率为22.49%,与模型预测值相比误差为10.89%;分禾阻力试验均方根为70.9 N,与模型预测值相比误差为7.78%。
Xinjiang is one of the most important high-quality cotton production areas in China,and sprayers with horizontal boom and hang boom are widely used in ripening and defoliation of the cotton.Due to the close planting cultivation of cotton,in the lower part of the cotton canopy,the spraying coverage of the defoliant is low and defoliation effect is poor,which seriously affects the cotton quality. In order to improve the spraying coverage rate of the defoliant in the middle and lower cotton,a scheme for optimizing the parameters of the divider was put forward,and it was designed and developed by using BoxBehnken. The parameters,such as top rake of the crop divider,ground clearance,field speeds were taken as the influencing factors,and spray coverage and resistance of crop divider were used as test indices in the experimental study,obtaining the test indices though field test with test equipment designed. By using the ellipsoidal basis function neural network（ EBFNN） the relationship between the indices and test factors was approached,then accurate and reliable approximation model was established.Then the multi-objective genetic algorithm was used to optimize the coverage rate and resistance of crop divider based on this approximate model in Isight software platform,the optimal parameters combination was obtained through determining the weight coefficient of the optimized solution set. Best combination of test parameters were listed below： ground clearance of the crop divider was 210 mm,the top rake of the crop divider was 12°,and the operation speed of the sprayer was 4 km / h. Field experiments were carriedout under this condition,the results show that the average droplet coverage on cotton canopy was22. 49%,compared with the model prediction,the error range was less than 10. 89%,and the root mean square value of grain resistance test was 70. 9 N,the error range was less than 7. 78%. It can provide a reference for cotton crop divider design and spraying parameters optimization of boom sprayer,and also greatly promote the progress of cotton defoliation harvesting mechanization.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2016年第5期62-69,共8页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家公益性行业(农业)科研专项(201203025)
农业部948引进重点项目(2011-G10(4))
关键词
棉花脱叶剂
喷雾机
分禾器
近似模型
优化
cotton defoliation
sprayer
crop divider
approximate model
optimization
