联合收获机脱粒滚筒角速度控制优化设计——基于小波神经网络  

Ptimization Design of Angular Velocity Control of Threshing Cylinder in Combine Harvester Based on Wavelet Neural Network

作　　者：李鑫[1] 孙祥云[1] 李凌雁[1] 

机构地区：[1]邢台职业技术学院,河北邢台054035

出　　处：《农机化研究》2016年第11期64-68,共5页Journal of Agricultural Mechanization Research

基　　金：国家自然科学基金青年基金项目(51305152)

摘　　要：脱粒滚筒是联合收获机的核心部件,其性能决定了联合收获机的工作质量和生产效率。由于不同地块和不同作物的湿度、密度不同,联合收获机的行走速度和喂入量也不同,因此脱粒滚筒的转速也应做出适当的调整,使滚筒的线速度保持在一个有较好脱粒效果的状态。为此,提出了一种新的双滚筒脱粒滚筒结构,该结构利用传感器采集滚筒信息,形成了滚筒转速的闭环反馈调节机制,并采用小波神经网络算法对转速的精度进行调节,提高了脱粒滚筒的作业精度。最后,对基于小波神经网络算法的双滚筒脱粒滚筒的性能进行了实验测试和仿真模拟,测试和仿真模拟得到的籽粒破碎率基本吻合,验证了实验的可靠性。对滚筒的脱净率进行了进一步的实验测试发现,利用神经网络算法和小波神经网络算法的脱粒滚筒脱净率都比较高,且小波算法要比单纯使用设计网络算法脱净率高。As the core part of the combine harvester,the threshing cylinder's performance determines the work quality and the production efficiency of the combine harvester. Due to the different plots and the humidity of different crops,different density,combine harvester walking speed and feed rate are also different. Therefore,the threshing roller cylinder rotation should also make appropriate adjustments,and the linear speed of the roller keep in a good threshing effect state.It puts forward a new double drum threshing cylinder structure,which was used to collect drum information,form a closed loop feedback control mechanism of cylinder speed. The wavelet neural network algorithm can adjust the speed accuracy,improve the operation accuracy of the threshing cylinder. Finally,based on the wavelet neural network algorithm,the experimental test and simulation was done to test the performance,which obtained grain crushing rate tallied to verify the reliability of the experimental. On the drum of threshing rate of further experimental tests found that by using neural network algorithm and wavelet neural network algorithm of threshing cylinder threshing rate is high,which can make the simple use of the algorithm of network design higher threshing rate.

关 键 词：联合收获机 脱粒滚筒 神经网络 小波算法 脱净率 

分 类 号：S225[农业科学—农业机械化工程]