Robotized laser beam welding of closed-square-butt joints is sensitive to the positioning of the laser beam with respect to the joint since even a small offset may result in a detrimental lack of sidewall fusion. An evaluation of a system using a photodiode aligned coaxial to the processing laser beam confirms the ability to detect variations of the process conditions, such as when there is an evolution of an offset between the laser beam and the joint. Welding with different robot trajectories and with the processing laser operating in both continuous and pulsed mode provided data for this evaluation. The detection method uses wavelet analysis of the photodetector signal that carries information of the process condition revealed by the plasma plume optical emissions during welding. This experimental data have been evaluated offline. The results show the potential of this detection method that is clearly beneficial for the development of a system for welding joint tracking.

Robotized laser beam welding of closed-square-butt joints is sensitive to how the focused laser beam is positioned in relation to the joint, and existing joint tracking systems tend to fail in detecting the joint when the gap and misalignment between the work pieces are close to zero. A camera-based system is presented based on a high dynamic range camera operating with LED illumination at a specific wavelength and a matching optical filter. An image processing algorithm based on the Hough transform extracts the joint position from the camera images, and the joint position is then estimated using a Kalman filter. The filter handles situations, when the joint is not detectable in the image, e.g., when tack welds cover the joint. Surface scratches, which can be misinterpreted as being the joint, are handled by a joint curve prediction model based on known information about the nominal path defined by the robot program. The performance of the proposed system has been evaluated off line with image data obtained during several welding experiments.