Forecasting Deep Dragging Blank Holder Force of Cupshell Based on Support Vector Machine

Blank holder force(BHF) forecasting is an important research direction in sheet metal forming. Support vector machine(SVM) is a novel learning machine based on the principle of structural risk minimization, which can solve the shortcoming of artificial neural networks, such as local optimization solution, lack generalization. In the study, SVM is presented to blank holder force forecasting. Cupshell which is a typical drawing workpiece is taken as the research object. The experimental results show that the proposed SVM provides better prediction capability for blank holder force forecasting than BP neural network. Therefore, SVM is considered as a promising alternative method for blank holder force forecasting.