【作者】 季彬彬；

【导师】 陈进；

【作者基本信息】 江苏大学 ， 机械设计及理论， 2005， 硕士

【摘要】 论文分析了联合收割机脱粒滚筒实际工作过程中的功耗,确定了联合收割机脱粒滚筒转速与喂入量之间的关系,提出通过稳定喂入量来稳定脱粒滚筒的转速,以提高联合收割机的工作效率。 在喂入量测定方面,本文利用喂入主动轴扭矩来实时反应倾斜输送器喂入量,并在DF—1.5型物料脱粒、分离仿真与控制试验台上,通过试验获得喂入主动轴扭矩和与之对应的喂入量值,建立了喂入量和喂入主动轴扭矩间的关系方程。 根据测得的喂入量,通过计算获得作物密度,但联合收割机是一个非线性时变且有大延时的系统,特别是要根据传感器检测的状态去控制联合收割机的工作过程时,存在着严重的时间滞后问题,鉴于此,本文提出了喂入量预测控制系统,根据从喂入主动轴检测到的作物密度信息对割台处作物密度作出合理预测,并根据预测结果调整联合收割机前进速度,以保持喂入量稳定。 在预测系统的构建方面,本文使用负荷预测理论中的模糊神经网络技术,并根据具体应用对象对预测系统的输入、输出量及其模糊分割、模糊规则库的建立进行了详细探讨,设计了网络的拓扑结构。 论文在DF—1.5型物料脱粒分离仿真与控制试验台上进行了水稻脱粒分离试验获得了作物密度及其变化的相关数据,从中选取训练样本和测试样本,提取出了初始模糊规则。同时,在利用MATLAB建立了联合收割机喂入量预测系统的模糊神经网络结构模型以后,对网络进行了训练和泛化能力检测,结果表明,建立的预测系统是可行的。 最后,对联合收割机喂入量预测系统进行了仿真试验,通过对比在联合收割机前进速度的调整中加入喂入量预测系统和未加入喂入预测系统两种情况下的结果,表明本文设计的喂入量预测系统是行之有效的。更多还原

【Abstract】 This paper analyzed the power consumption of the threshing cylinder and decided the relationship between the rotating speed and the threshing cylinder and the feed quantity . On the base, in order to raise the efficiency of the combine harvester, this paper suggested to stabilize the rotating speed by adjusting the feed quantity to a stable amount.In the part of measuring feed quantity, this paper used the torque of driving axle of the feed system to reflect the feed quantity and got the equation of the torque and feed quantity by experiment which was carried out by the "simulation and control test equipment DF-1.5 for grain threshing and separating".When measuring feed quantity, this paper calculated the density of grain. But the combine harvester was a delayed, non-linear and time varying system. Particularly when the automatic control system of the combine adjusted the working parameters according to the signal got from the sensors, the problem of delay became more obvious. So this paper designed a predictive system to forecast the density of grain nearby the headers on the ground of density got from the torque of driving axle of the feeding system and adjust the forward speed of combine harvester according to the result forecasted by the predictive control system.Appling the technology of Fuzzy Neural Network, this paper construct the predictive system according to the actual destination and then decided the input and output of the network and its fuzzy dividing. At the same time, this paper investigated the constructing of fuzzy rule base and designed the topological structure of networks.This paper carried out the experiment of paddy threshing and separating by using "simulation and control test equipment DF-1.5 for grain threshing and separating", and got the data about the density and its variation of paddy. From these data, the paper selected the example data for training 、 test and abstracting initial fuzzy rules. At the same time, after constructing the fuzzy neural network of predictive system using the software of MATLAB, this paper trained the network using the example data and checked the generalizing ability of the network. The result proved thenetwork of predictive system to be practicable.At the end, this paper carried out the simulation experiment using the predictive system of combine. At this experiment, this paper contrasted the effect of adjustment of the automatic control system in which the predictive system was or was not added, the result of simulation experiment proved the predictive control system to be effective.更多还原