Prediction of springback in sheet metal components with holes on the bending area, using experiments, finite element and neural networks

摘要

The springback phenomenon has a significant role in precision sheet metal bending. Traditionally, the designers obtain the values for springback for different materials and bending parameters from handbook tables or springback graphs. However these tables or graphs cannot be used for perforated components which are parts with holes on the bending surfaces. This paper presents the results of research in wipe bending for perforated components. In the present research the influence of process variables such as hole type, number of holes, the ratio of hole width to sheet width, die radius and pad force on springback are discussed. Some experiments are carried out on HSLA360 and Stl2 materials which show that the presence of holes on the bending area can affect the springback considerably. These experiments are also simulated by finite element method. The results of the finite element model used, compared with experiments show the reliability of the proposed model. These results are also used as the training data for two artificial neural networks. The first network is used for one type of hole and the second one for three types of holes. After testing both networks the results show that the latter is more accurate to predict the springback.