田间作物表型获取无人车平台主体结构设计与优化

Design and optimization of main structure of unmanned vehicle-based field crop phenotyping platform

本研究旨在设计和优化一种稳定、轻量化的无人车载田间作物表型获取平台主体结构。为了满足高安全性、高稳定性、轻量化的要求,采用Pro/Engineer Wildfire 5.0软件设计无人车平台主体结构模型,并采用HyperWorks 2020软件进行有限元分析和结构模型优化。同时,在设计过程中对结构进行静力学和动力学分析。以结构整体质量最小化为目标函数,以材料屈服强度和一阶模态为约束条件,采用试验设计法提取多工况下对一阶模态和应力敏感的部件结构参数作为设计变量,大大减少了变量数量。应用自适应响应面法进行迭代计算,优化获取自适应的结构变量。与有限元模型的对应输出响应相比,自适应响应面近似模型在主体结构质量和一阶模态频率的误差分别为3.79%和4.32%,在静止与匀速、启动、停车工况下的最大应力误差分别为4.24%、4.14%和1.26%,表明自适应响应面近似模型具有满足设计要求的精度且误差均低于5%。相比于优化前的主体结构,在保持各工况安全系数在5.0以上的情况下,实现整体质量减少63.61%,得到了安全系数高、稳定性强的田间作物表型获取平台主体结构。

This study aims to design and optimize the main structure of a stable and lightweight unmanned vehicle-based field crop phenotyping platform.In order to meet the requirement of high safety,high stability,and lightweight,Pro/Engineer Wildfire 5.0 software was used to design the main structure model of the platform,and HyperWorks 2020 software was employed to perform the finite element analysis and optimize the structure model.Meanwhile,the statics and dynamics analysis of the structure was implemented during the design process.Taking the main structural mass as the objective function,with the material yield limit and the first-order mode as the constraints,the design of experiment(DOE)method was applied to extract the structural parameters of parts with the high sensitivity to the first-order mode and stress under multi-working conditions as design variables,which greatly reduced the variable number.Then,the adaptive response surface method(ARSM)was applied for iterative calculation to obtain the optimal variables.Compared with the corresponding output response of the actual finite element model,the ARSM approximate model produced a low error of 3.79%and 4.32%in the main structure mass and the first-order modal frequency,respectively,which also obtained the maximum stress error of 4.24%,4.14%,and 1.26%under the static and uniform speed conditions,starting conditions,and emergency shutdown conditions,respectively.These results show that the ARSM approximate model has a high accuracy and the error is less than 5%.Compared with the original structure,the final overall mass was reduced by 63.61%at maintaining the safety factor of each working condition above 5.0.As a result,the main structure of field crop phenotyping platform is obtained with high safety factor and meeting usage requirements.