特种车辆伸缩臂力学特性分析与多目标优化设计OA

To improve static and dynamic performance and lightweight design of forklift telescopic booms,this paper proposes a multi-objective optimization method based on hybrid surrogate model and combined weighting-grey correlation method.Taking the cross-sectional parameters of the telescopic boom as input variables,this paper employs Spearman correlation analysis to identify the design variables that markedly influence the output responses.Using mass,total deformation,maximum stress,and second-order modal frequency as responses,a RBFNN-RSM hybrid surrogate model is built and combined with the NSGA-Ⅱ algorithm to perform multi-objective optimization of the telescopic boom.For the Pareto solution set generated by the optimization,a game theory-based subjective-objective weighting method is employed to determine the weights of the output responses.All non-dominated Pareto solutions are ranked by the gray correlation analysis to select the global optimal solution.Results show the mass of the optimized telescopic boom is down by 15.22%whereas the second natural frequency is up by 7.59%compared with the original design.