摘要
Abstract
In this paper,the multi-objective optimization of the cross-section of telescopic boom of a telescopic aerial work vehicle was performed to minimize the mass of the telescopic boom and ensure safety.Firstly,a three-dimensional model of aerial work vehicle was established and its rigidity and strength were analyzed.Then,working condition analysis was conducted,and a luffing angle of 53 degrees of the telescopic boom was determined as the most dangerous working condition.Under this working condition,the approximate model of the telescopic boom section optimization model was constructed by radial basis function neural network.In order to minimize the mass and deformation,NSGA-Ⅱgenetic algorithm was used to optimize the solution,and the optimal proposal of telescopic boom section was obtained,and the lightweight optimization of telescopic boom was completed.关键词
高空作业车/伸缩臂/有限元分析/神经网络/NSGA-ⅡKey words
aerial work vehicle/telescopic arm/finite element analysis/neural network/NSGA-Ⅱ分类
机械工程
