Welding torch attitude-based study of human welder interactive behavior with weld pool in GTAW

Abstract

Skilled human welder adjusts welding parameters including the welding torch attitude, moving speed and position to control weld quality and avoid weld defects based on real time observed varying weld pool surface for precision joining using gas tungsten arc welding (GTAW). However, welder behavior/adjustment appears to be a complex reactive response. To understand this complex response and develop intelligent robotic arc welding, a new scheme that correlated welding torch attitude to weld pool surface to study welder behavior in torch adjustment as response to weld pool was proposed and realized. The torch attitude and the 3D weld pool surface were synchronously measured using a wire inertial measuring unit (IMU) and a laser vision-based approach. An image processing algorithm was developed to extract the characteristic parameters of the weld pool surface from the laser stripes reflected by the specular pool surface. The improved quaternion-based unscented Kalman filter was used to estimate the torch orientation from its inertial measurement data, showing that the torch attitude has been obtained with an acceptable error in the order of 1°(x axis and y axis) and 2°(z axis). Several experiments were performed and the correlation of the corresponding data was detailed. It indicates that the change of torch attitude represents the welder's operating skills, welding experience and smart decision. The three characteristic parameters reflect the welder's reactive response on the torch adjustments. The curvature radius of laser stripes can predict the changing trends of the weld pool surface, providing the needed information for welders to make a smart decision. The proposed scheme is feasible for measuring and analyzing the welder's skills and experience.