A Study of Predicting Method of Residual Stress Using Artificial Neural Network in $CO_2$ Arc Welding

인공신경회로망을 이용한 탄산가스 아크 용접의 잔류응력 예측에 관한 연구

  • 조용준 (한양대학교, 정밀기계공학과 대학원) ;
  • 이세헌 (한양대학교 정밀기계공학과) ;
  • 엄기원 (한양대학교 정밀기계공학과)
  • Published : 1995.09.01

Abstract

A prediction method for determining the welding residual stress by artificial neural network is proposed. A three-dimensional transient thermomechanical analysis has been performed for the CO$_{2}$ arc welding using the finite element method. The first part of numerical analysis performs a three-dimensional transient heat transfer analysis, and the second part then uses the results of the first part and performs a three-dimensional transient thermo-elastic-plastic analysis to compute transient and residual stresses in the weld. Data from the finite element method are used to train a backpropagation neural network to predict the residual stress. Architecturally, the fully interconnected network consists of an input layer for the voltage and current, a hidden layer to accommodate the ailure mechanism mapping, and an output layer for the residual stress. The trained network is then applied to the prediction of residual stress in the four specimens. It is concluded that the accuracy of the neural network predicting method is fully comparable with the accuracy achieved by the traditional predicting method.

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References

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