The Simulation of Metal Sheet Pressing Based on ANN

Author

Zhaohu, Deng ; Yanqin, Zhang ; Yuping, Huang ; Feng, Ruan

Author_Institution

South China Univ. of Technol., Guangzhou

Volume

2

fYear

2007

Firstpage

70

Lastpage

74

Abstract

Pressing formation involves complicated mechanical theory; it is hard to analysis the stress situation with analytical method. Based on the theory of artificial neural networks, the stress situation of metal sheet was studied in this paper. This paper attempted to establish a nonlinear model with GRNN. This model would simulate the parts pressing. For building the GRNN model, the technology of parameter-FEM analysis was adopted in this paper. With this technology the GRNN would be used to build the model of metal sheet pressing in place of FEM. At the same time as certification the pressing of a complicated part was simulated in this paper. Through comparing the simulation results to original data, it shows that the model with GRNN can reflect the stress situation of metal sheet pressing accurately. At the same time this technology provides an effective method for further optimization of the parameters.

Keywords

finite element analysis; neural nets; pressing; production engineering computing; sheet metal processing; ANN; artificial neural networks; mechanical theory; metal sheet pressing; nonlinear model; parameter-FEM analysis; Artificial neural networks; Automobile manufacture; Certification; Computer industry; Design automation; Equations; Optimization methods; Pressing; Sheet materials; Stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2007. ICNC 2007. Third International Conference on

Conference_Location

Haikou

Print_ISBN

978-0-7695-2875-5

Type

conf

DOI

10.1109/ICNC.2007.744

Filename

4344318