AN ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEM FOR PREDICTING SPRINGBACK OF U-BENDING

作者：Lin Bor Tsuen^*; Huang Kun Min

来源：Transactions of the Canadian Society for Mechanical Engineering, 2013, 37(3): 335-344.

DOI：10.4028/www.scientific.net/amm.284-287.25

• U-bending
• springback
• adaptive-network-based fuzzy inference system
• sheet metal forming

Springback will occur when the external force is removed after bending process in sheet metal forming. This paper proposed an adaptive-network-based fuzzy inference system (ANFIS) model for prediction the springback angle of the SPCC material after U-bending. Three parameters were selected as the main factors of affecting the springback after bending, including the die clearance, the punch radius, and the die radius. The training data were obtained from results of U-bending experiment. The training data with four different membership functions triangular, trapezoidal, bell, and Gaussian functions were employed in the ANFIS to construct a predictive model for the springback of the U-bending. After the comparison of the predicted value with the checking data, the results show that the triangular membership function has the best accuracy, which make it the best function to predict the springback angle of sheet metals after U-bending.

• 出版日期2013