Optimization of Variable Blank Holder Force for Electromagnetic Blank Holding Technology

Abstract

For eliminating wrinkling during sheet metal drawing process, Blank Holder Force (BHF) is always applied conventionally. Conventional blank holding technologies usually create drawing defects because that the types of BHF created by them are always limited. Besides, the tendency of VBHF is always hard to be determined. To resolve the difficulty, a strategy of optimizing Variable Blank Holder Force (VBHF) is proposed in this study. The optimizing algorithm of searching reasonable VBHF is combined with Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA). The impact of BPNN is to construct the network between BHF nodes and the maximum thinning reduction ratio. The usage of GA is to search for reasonable VBHF with trained BPNN. For realizing the application of the optimized VBHF, an Electromagnetic Blank Holder Device (EBHD) for conventional drawing is utilized. To validate the feasibility of the optimized VBHF, corresponding numerical simulations about cylindrical part drawing process are conducted at first. Additionally, corresponding experiments have also been implemented with the usage of optimized VBHF and constant BHF. Eventually, it can be concluded that the application of optimized VBHF can more effectively restraining the thinning rate of cylindrical part. Besides, the application prospect of proposed VBHF optimizing strategy has been also illustrated at last.