Measurement of Molten Pool Shape and Penetration Control Applying Neural Network in TIG Welding of Thin Steel Plates.

Abstract

An intelligent welding robot system with visual sensors is developed in order to realize full automatic welding of thin mild steel plates including automatic seam tracking and automatic control of welding conditions. A system to detect the shape and dimension of molten pool using CCD camera and a penetration control system using Neural Network in TIG arc welding are investigated. In order to characterize the shape of molten pool, width, length and area of the molten pool were measured, and are used to form the contour of the molten pool as shape parameters. These parameters are input to the neural network, which outputs optimum welding conditions to control the penetration of the molten pool. Consequently, if unexpected changes occur in welding conditions, such as root gap, welding speed and so on, the welding system 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.