杨忠堡村牛羊养殖特色主导产业发展规划

作为“整村推进”的“科技扶贫”工作人员,在当地主导产业发展规划的制定中,必须要通过认真地调查研究,依据当地生产力发展的基本条件、发展现状及发展趋势等,科学利用资本积累及运行发展的基本规律,坚持“扬长补短、发挥优势,壮短益长、挖掘潜力,突出重点、优先发展”的基本原则,寻求能够促进当地生产力快速高效发展的方法和措施.介绍了杨忠堡村的概况,阐述了牛羊养殖特色主导产业规划的主导思想及生产内容,制定了产业发展方向和目标,并分析了预期经济效益.     

行星轮系水稻钵苗移栽机构正反求设计方法研究

为了解决现有行星轮系水稻钵苗移栽机构较难同时具备理想的移栽轨迹和姿态的问题,提出了正向设计与局部轨迹微调的反求设计相结合的设计方法。以非圆齿轮行星轮系水稻钵苗移栽机构的设计为例,阐述该方法的实现过程。建立行星轮系水稻钵苗移栽机构设计要求,并分析其工作原理,在前期正向设计的基础上,局部调整其移栽静轨迹,通过反求设计进一步优化设计移栽机构。进行局部反求设计的运动学分析和运动学建模,基于Matlab平台开发计算机辅助设计软件,通过人机交互的方式得到移栽机构的机构参数,使其不仅满足移栽臂移栽的姿态要求,同时获得更理想的移栽工作轨迹。根据最终得到的机构参数设计移栽机构结构,完成三维建模、虚拟仿真试验,加工、装配移栽机构物理样机,完成了高速摄像运动学试验。将移栽机构理论计算、虚拟仿真、样机试验得到的移栽静轨迹比较,同时逐一将轨迹相关参数、取秧角、推秧角、角度差等设计目标参数与相应数值化目标进行对比,结果显示,均满足要求,验证了设计方法的正确性。与以往单一的正向设计、反求设计方法相比,该方法设计的移栽机构不仅具有更优的移栽工作轨迹,也可满足较好的移栽姿态要求。     

Study on Dynamical Characteristic of Epicyclic Gear Drive with Internal Tooth

The epicyclic gear drive with internal tooth is analysed,a dynamic analysis model which is based on the compatibility conditions of deformation is set up.On the basis of this model,the analysis of dynamics and kinematics is made,and the influence of design parameters on dynamical characteristic is also studied.     

空间机构连杆的运动分析

建立了空间连杆机构的分析模型,利用矢量回转法确定了空间机构连杆上沿任一直线作匀速运动的动点轨迹矢量方程,即动点轨迹方程,并进一步地对矢量方程进行微分求出动点在任一瞬时时刻的速度和加速度;建立了空问机构连杆上任一直线的轨迹曲面方程,即连杆曲面方程;再应用MATLAB函数绘制了空间机构连杆上任一直线上动点的轨迹曲线、速度和加速度图以及连杆曲面图,为空间机构研究和机器人设计提供了理论基础.     

一般6R机器人的高精度逆运动学优化算法

为提高一般6R机器人逆运动学算法的精度和效率,提出一种基于符号运算和矩阵分解的优化算法。对6个基础逆运动学方程作变换,采用符号运算预处理得到14个逆运动学方程,避免大量浮点数计算累积误差。利用其中6个方程与关节变量3无关的特点,将目标矩阵从24阶降低到16阶,包含的关节变量从3个增加到4个。把一元16次方程求根问题转换为矩阵特征分解问题,并选取较高数量级的相关数据元素计算关节变量,进一步提高了算法精度。以一般6R机器人为例,求解结果表明,提出的算法能够得到具有任意期望精度的最多16组实数逆运动学解。     

油葵收获割台工作性能仿真及试验研究

为研究油葵收获割台在工作过程中的性能与可靠性,得到该割台正常工作时的关键参数,利用SOLIDWORKS对割台进行三维参数化建模并导入ADAMS中进行运动学仿真,得到收获时茎秆受力和摆动程度的仿真结果并进行正交组合分析,仿真和分析结果表明:割台正常工作最优参数的组合是拉茎辊转速800 r/min、机器的行驶速度2.12 km/h、拉茎间隙10 mm、拉茎辊的倾角20°,同时往复切割刀的切割速度2 m/s时茎秆的受力最小,通过田间试验发现整个收获过程籽粒损失率≤3%,喂入输送绞龙的茎秆较短,收获可靠性较好,结果表明该割台适合油葵的机械化收获。     

基于改进蚁群算法的3-PPR并联机构位置正解研究

针对3-PPR并联机构位置正解问题,运用螺旋理论计算其自由度,并分析其运动特性,同时通过解析法构建该并联机构的完整运动学逆解。将并联机构运动学正解问题的求解转化为对目标函数优化问题的求解,并基于此建立该并联机构正解的目标函数优化模型。通过对基本蚁群算法进行有效的改进,构建了可用于求解连续优化问题的改进蚁群算法。运用该算法求解3-PPR并联机构的运动学正解并进行Matlab仿真分析,对比传统数值方法和改进蚁群算法,证实该算法具有良好的全局寻优能力,并能避免初值和局部最优值对计算结果的影响,可有效应用于求解并联机构的位置正解问题。     

Neural network prediction of performance parameters of an inclined plate seed metering device and its reverse mapping for the determination of optimum design and operational parameters

Seed planting equipment with inclined plate seed metering devices is the most commonly used equipment for planting of peanut crop in India. For obtaining the high yield, it is very essential to drop the peanut seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on forward speed of the planting equipment, rotary speed of the metering plate and area of cells on the plate. The relationship between these factors and the performance parameters viz., seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and may pose difficulty in the determination of inputs for a set of desired outputs (reverse mapping). Hence, an attempt has been made in this paper to develop the feed forward artificial neural network (ANN) models for the prediction of the performance parameters of an inclined plate seed metering device. The data were generated in the laboratory by conducting experiments on a sticky belt test stand provided with a seed metering device and an opto-electronic seed counter. The generated data was used to develop both statistical and neural network models. The performance of the developed models was compared among themselves for 4 randomly generated test cases. The results show that the ANN model predicted the performance parameters of the seed metering device better than the statistical models. In order to determine the optimum forward speed of the planting equipment, peripheral speed of the metering plate and the area of cells on the plate to obtain the recommended seed rate of 33.33 seeds/m², seed spacing of 100 mm and percent seed damage of 0.2% with 100% fill of the cells, a novel technique of reverse mapping using ANN model was followed. It was observed that the optimum forward speed of the planting equipment and optimum area of cells on the metering plate had good correlation with size of seed. Linear regression equations were developed to predict the optimum forward speed of the planting equipment and optimum area of cells on the metering plate using the size of seeds as independent parameter. The peripheral speed of the metering plate of 0.237 m/s was found to be optimum for the size of seeds in the range of 95.42-123.01 mm². However, the results need to be verified by conducting planting operation under actual field conditions.