| Electromagnetic forming is a high speed forming method that metal is plasticallydeformed by strong pulsed magnetic force, and compared with the traditionalprocessing technology, has more advantages.However, limited by energy, strength ofcoil and the deformation mode of sheet metal, it is difficult to be applied in the deepdrawing and precise forming of large aluminum alloy plates. In this paper, based on theprevious studies, in the electromagnetic pulsed deep drawing process of sheet metal, amethod has been adopted to make flange materials of the parts flow in the radialdirection. A forming process with characteristics combining the deep drawing-bulgingforming has been formed, and the limit of deep drawing can be improved.In this paper, the sequential coupling method was used in the ANSYS software tobuild the3D finite element model for the electromagnetic deep drawing of5052aluminum sheet, the forming process has been simulated, and the simulation results hasbeen analyzed. The deformation characteristics of the5052aluminum alloy plates inthe electromagnetic deep drawing process has been obtained, the energy efficiency hasbeen improved. This simulation method considers the effect of workpiece deformationon the magnetic field distribution, can improve the calculation precision of iterativecoupling analysis between the electromagnetic field and structure field.The electromagnetic deep drawing process has been studied.The electromagneticdeep drawing experimental platform has been built, and the simulation method hasbeen verified by experiments; the forming limit criterion of sheet metal and influentialfactors of the limit drawing height have been studied; process parameters have beenoptimized by use of numerical simulation, then the limit of deep drawing has beenfurther improved and a larger height can be obtained.The influence law of blank diameter, discharge voltage, die fillet radius, blank holder gap and friction coefficient for deep drawing height and forming quality hasbeen studied through orthogonal experiment.The simulation results have been analyzedby range and variance analysis, the optimal combination of process parameters hasbeen obtained, and the significance of each factor has been analyzed, which canprovide direction for the further optimization. Finally, according to the results oforthogonal experiment, a BP neural network model for deep drawing height has beenbuilt, and the reliability of the model has been verified. |
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