关键词: 板料成形, 随机聚焦搜索算法, 工艺参数优化, 数值模拟, 正交试验, 反向传播神经网络训练

Abstract: Aiming at the problem of sheet metal stamping process optomization，a kind of swarm intelligence algorithm was studied.The training samples for neural network were obtained by combining numerical simulation technology with orthogonal experiments，and the objective function model of Stochastic Focusing Search (SFS) algorithm was constructed by using back propagation neural network.On the basis of this function model，SFS algorithm was used to optimize the sheet stamping process parameters.By taking a deep box-shaped workpiece for instance，the optimized process parameters were input into eta/DYNAFORM simulation model to validate this algorithm，and the result showed that good forming quality was obtained.To further verify the advantages of SFS algorithm in efficiency and optimization of global searching，the genetic algorithm's optimal result was compared with SFS.The result showed that SFS was a better optimization algorithm in sheet stamping process parameter optimization respect.

Key words: sheet stamping, stochastic focusing search, process parameters optimization, numerical simulation, orthogonal experiment, back propagation network training