摘要
以铝合金U型材的回弹作为研究对象,采用正交实验法设计安排模拟实验,通过有限元软件成功地模拟了工件成形和回弹的实际过程,分析了影响工件滚弯成形的主要因素。将模拟的结果作为人工神经网络的训练样本,建立了单轴柔性滚弯成形过程的神经网络预测模型,并通过实验值检验预测结果;结果表明预测值和实验值的偏差很小。由此证明,将正交实验、数值模拟与神经网络3者相结合可以较好地预测单轴柔性滚弯成形的回弹,提高工艺参数设计效率。
One-axle rotary shaping with the elastic medium （RSEM） is a kind of advanced sheet metal forming process. Our purpose is to predict the springback of aluminous U-section. The orthogonal method is used to arrange the simulation experiments, and the forming and springback of the workpiece are simulated successfully with a finite element simulation software. The main factors that influence the RSEM are analyzed. The simulation results are used as the training samples of the artificial neural network （ ANN）, and the ANN prediction model of RSEM process is set up. The prediction results are tested with the experiment data, and only a little tolerance exists between the two values. It demonstrates that the combination of orthogonal test, numerical simulation and neural network can effectively predict the springback of RSEM, and that the design efficiency of process parameters can be improved.
出处
《机械科学与技术》
CSCD
北大核心
2009年第4期464-467,共4页
Mechanical Science and Technology for Aerospace Engineering
关键词
单轴柔性滚弯
神经网络
回弹
有限元模拟
预测
one-axle rotary shaping
neural network
springback
finite element simulation
prediction
