Measurement of molten pool shape and penetration control applying neural network in TIG welding of thin steel plates

An intelligent welding robot system with visual sensors is developed in ord er to realize full automatic welding of thin mild steel plates including au tomatic seam tracking and automatic control of welding conditions. A system to detect the shape and dimension of molten pool using CCD camera and a pe netration control system using Neural Network in TIG are welding are invest igated. In order to characterize the shape of molten pool, width, length an d area of the molten pool were measured, and are used to form the contour o f the molten pool as shape parameters. These parameters are input to the ne ural network, which outputs optimum welding conditions to control the penet ration of the molten pool. Consequently, if unexpected changes occur in wel ding conditions, such as root gap, welding speed and so on, the welding sys tem can optimumly control the welding conditions. The constructed system is tested and found to be effective for penetration control in automatic butt welding of thin mild steel plates.