Transactions of Materials and Heat Treatment

Title：Defects prediction by artificial neural network based on FEM simulation

Authors： Shanghai Jiaotong University Zhang Xingquan Peng Yinghong Ruan Xueyu Northwestern Polytechnical University Li Miaoquan Wu Shichun

Unit：

KeyWords： Defect predection FEM simulation Artificial neural network

ClassificationCode：TP18,O242.1

year,vol(issue):pagenumber：1998,23(3):0-0

Abstract：

In this paper,the compressible rigid plastic finite element method(FEM) is used to simulate the deformation process of a cylindrical upsetting of porous material A successful analysis of forging process results in the prediction of stress,strain and density fields,which can be used together with the ductile fracture criterion obtained by Lee and Kuhn to check for possible defects Then it describes the application of artificial neural networks(ANN) used for defect prediction A defects prediction system based on the ANN and FEM is established,and the learning samples are gained from the results combining the rigid plastic finite element method(FEM) with the Lee Kuhn's criterion Then limit process parameters are obtained through this system The result shows that the method is effective for defects prediction

Funds：

上海市科技启明星计划资助项目

Reference：

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