Proceedings of the 1997 conference on Advances in neural information processing systems 10
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
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It is difficult to predict the mechanical properties of welded joints because of non-linearity in welding process and complicated mutual effects in multi composition welding material. Based on these practical problems, the application of neural network technology in predicting mechanical properties of welding joints is developed. The modeling method has been studied and the author puts forward that the parameters of neutral network can be optimized by the method of uniform design. The neutral network model of mechanical properties of welding joints is established on the basis of the data of welding thermal simulation, and the experimental results show that this model can predict the mechanical properties including impact toughness, tensile strength, subdued strength, reduction ratio of area and hardness more accurately. At the same time, using this method can improve estimating precision largely compared with using traditional statistic method. That is, this method provides an effective approach to estimate the mechanical properties of welding joints.