In-process computer vision monitoring of laser welding for Strenx 700 E high-strength steels

This study presents an integrated approach for monitoring and characterizing autogenous laser welding of Strenx 700 E high-strength steels, aiming to enhance weld quality and process reliability. A multisensory monitoring system was developed, incorporating a laser illumination welding camera with a computer vision algorithm based on morphological transformations to extract keyhole contours and analyze capillary wave behavior. Optical coherence tomography was employed to reconstruct internal keyhole geometry, providing valuable insights into subsurface features and melt pool dynamics. Additionally, an optical microphone exhibited a correlation between spectral magnitude and laser power in bead-on-plate welds. Metallurgical analysis, including cross-sectional examination and Vickers hardness testing, revealed complete penetration and good weldability at higher laser powers, with moderate to high hardness observed in the fusion and heat-affected zones. The findings illustrate the advantages and complementarity of advanced monitoring techniques, offering improved quality assurance and facilitating further advancements for more reliable and efficient laser welding processes in industrial applications requiring durable joints.