Journal of Welding and Joining

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Journal of KWJS. 2007;25(5):64-70. Published online January 28, 2008.
A Study on Real-time Prediction of Bead Width on GMA Welding
Joon-Sik Son, Ill-Soo Kim, Hak-Hyoung Kim
Abstract
  Recently, several models to control weld quality, productivity and weld properties in arc welding process have been developed and applied. Also, the applied model to make effective use of the robotic GMA(Gas Metal Arc) welding process should be given a high degree of confidence in predicting the bead dimensions to accomplish the desired mechanical properties of the weldment. In this study, a development of the on-line learning neural network models that investigate interrelationships between welding parameters and bead width as well as apply for the on-line quality control system for the robotic GMA welding process has been carried out. The developed models showed an excellent predicted results comparing with the predicted ability using off-line learning neural network. Also, the system will extend to other welding process and the rule-based expert system which can be incorporated with integration of an optimized system for the robotic welding system.

Keywords :Real-time monitoring;GMA welding;Neural network;Welding quality

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