APPLICATION OF ARTIFICIAL NEURAL NETWORK TO INVERSE PROBLEMS OF ESTIMATING INNER ETCH OF ELASTOPLASTIC PIPE UNDER PRESSURE  

作　　者：Guan, BT Shen, CW Xiao, JS Cai, YS 

机构地区：[1]WUHAN TRANSPORTAT UNIV,WUHAN 430063,PEOPLES R CHINA

出　　处：《Acta Mechanica Solida Sinica》1996年第1期88-93,共6页固体力学学报（英文版）

摘　　要：To determine a variation of pipe's inner geometric shape as due to etch, the three-layered feedforward artificial neural network is used in the inverse analysis through observing the elastoplastic strains of the outer wall under the working inner pressure. Because of different kinds of inner wail radii and eccentricity. several groups of strains calculated with computational mechanics are used for the network to do learning. Numerical calculation demonstrates that this method is effective and the estimated inner wall geometric parameters have high precision.To determine a variation of pipe's inner geometric shape as due to etch, the three-layered feedforward artificial neural network is used in the inverse analysis through observing the elastoplastic strains of the outer wall under the working inner pressure. Because of different kinds of inner wail radii and eccentricity. several groups of strains calculated with computational mechanics are used for the network to do learning. Numerical calculation demonstrates that this method is effective and the estimated inner wall geometric parameters have high precision.

关 键 词：artificial neural network inverse problem ELASTOPLASTIC finite element 

分 类 号：TH136[机械工程—机械制造及自动化]