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Welding Procedure for joint has a very important position in the manufacture of all kinds of important products. Application of neural network technology could improve the existing in welding procedure qualification for joint process. It is shown that the yield strength of welded joint could be predicted effectively by using the welding parameters of welded joint, the temperature of the welding parameters and the heat treatment after welding as the input parameters by the neural network training. But the P, B and S element could be ignored in the process of predicting yield strength due to little influence on yield stress. The yield strength of steel could be increased by the increase of C content, which could be decreased by the increase of the heat treatment temperature. Neural network model predicts the yield strength of materials with high accuracy, which could be utilized to the simulation of welding procedure qualification for joint. Keywords—neural network; yield stress; welded joint

Application of Neural Network Technology in Welding Procedure Qualification for Joint