关键词: 钻孔夹具, 薄板件, 定位布局, 变形, 多目标优化, 神经网络, 粒子群优化算法

Abstract: Considering the multi-objective attribute and excessive computational cost of finite element analysis during the optimization of drilling fixture locating layout,a multi-objective optimization method of drilling fixture locating layout based on Back Propagation Neural Network (BPNN) and Particle Swarm Optimization (PSO) was proposed.The maximum deformation and the overall deformation of the sheet metal part after drilling under different fixture locating layouts were obtained by finite element simulation analysis.The simulation results were taken as training samples to establish a multi-objective neural network prediction model between the locating layout and the maximum and overall deformation of the sheet metal part.On this basis,the Pareto optimal solution set of the fixture locating layout for drilling a single hole was obtained by taking the fixture locating layout as design variable and the maximum deformation and the overall deformation of workpiece as minimum objectives,and combining BPNN prediction model with PSO algorithm.The feasibility and effectiveness of the proposed method were verified by two cases of flat and curved plate.

Key words: drilling fixture, sheet metal part, locating layout, deformation, multi-objective optimization, neural network, particle swarm optimization algorithm