摘要
A new method was worked out to improve the precision of springback prediction in sheet metal forming by combining the finite element method (FEM) with the data mining (DM) technique. First the genetic algorithm (GA) was adopted for recognizing the material parameters. Then according to the even design idea, the suitable calculation scheme was confirmed, and FEM was used for calculating the springback. The computation results were compared with experiment data, the difference between them was taken as source data, and a new pattern recognition method of DM called hierarchical optimal map recognition method (HOMR) is applied for summarizing the calculation regulation in FEM. At the end, the mathematics model of the springback simulation was established. Based on the model, the calculation errors of springback can be controlled within 10% compared with the experimental results.
A new method was worked out to improve the precision of springback prediction in sheet metal forming by combining the finite element method (FEM) with the data mining (DM) technique. First the genetic algorithm (GA) was adopted for recognizing the material parameters. Then according to the even design idea, the suitable calculation scheme was confirmed, and FEM was used for calculating the springback. The computation results were compared with experiment data, the difference between them was taken as source data, and a new pattern recognition method of DM called hierarchical optimal map recognition method (HOMR) is applied for summarizing the calculation regulation in FEM. At the end, the mathematics model of the springback simulation was established. Based on the model, the calculation errors of springback can be controlled within 10% compared with the experimental results.
基金
ProjectsupportedbyFord-ChinaResearchandDevelopmentFoundation (GrantNo .97162 14
