基于人工神经网络的拼焊板成形极限图预测  

Prediction of forming limit diagram for tailor welded blanks based on artificial neural network

作　　者：陈水生[1] 唐春红[2] 

机构地区：[1]河南理工大学,焦作454000 [2]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082

出　　处：《塑性工程学报》2014年第4期47-51,共5页Journal of Plasticity Engineering

基　　金：河南省教育厅科学技术研究重点项目(14A460013);河南省科技攻关计划项目(142102210130)

摘　　要：成形极限图(FLD)是评价金属板材成形能力的重要工具。为快速的建立拼焊板(TWB)成形极限图,建立基于人工神经网络(ANN)拼焊板FLD的预测模型。采用试验设计和有限元法获得训练样本,L-M算法对样本数据进行训练,建立了FLD预测模型并与物理试验结果对比。基于预测模型,分析了摩擦系数对拼焊板最小极限应变的影响。结果表明,基于ANN预测的拼焊板FLD与试验结果吻合,主应变的相对误差最大为8.71%。摩擦系数f对最小极限应变影响较大,f从0增大到0.12时,最小极限应变先增大后减小,并在摩擦系数f=0.06附近出现极小值。The forming limit diagram （FLD） is a very effective tool to evaluate the formability of the sheet metal . To quickly create the FLD for tailor welded blank （TWB） ,we proposed a prediction model based on an artificial neural network .The design of experiment and finite element method were used to gain the training samples , which were trained by the Levenberg-Marquardt （L-M ） algorithm . The prediction model of FLD was built and validated using the experimental data . Furthermore , the effect of the friction coefficient on the minimum ultimate strain was analyzed by the presented prediction model . The results show the FLD by the prediction model is consistent with that from the experiment data ,and the maximum relative error between the experiments and the predictions is 8.71% . The friction coefficient has a marked effect on the limit strain of TWB . The least limit strain first increases then decreases with the increasing of the friction coefficient form 0 to 0.12 , reaching the minimal value when the friction coefficient is near 0.06 .

关 键 词：拼焊板 成形极限图 人工神经网络 预测模型 

分 类 号：TG386[金属学及工艺—金属压力加工]