Design and optimization of main structure of unmanned vehicle-based field crop phenotyping platform - TANG Zheng; YU Yue; LIU Yufei; CEN Haiyan (浙江大学学报. 农业与生命科学版)
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.