Rapid visual detection of laser welding defects in bright stainless steel thin plates

Abstract Stainless steel sheets with bright surfaces have been widely used in household appliances, decorative materials, highway and railway vehicles, and other fields. In order to reduce welding deformation while maintaining overall aesthetics, the commonly used welding method is laser welding. In laser welding, various welding defects are the main causes of weld failure. At present, the main detection method for defects in such slender welds is laser structured light visual scanning detection. However, due to the fact that the reflection of high gloss stainless steel material is mainly mirror reflection, there will be a substantial amount of signal loss in structured light visual inspection. This article proposes a characterization and detection method for the surface morphology and defects of laser welding of high reflective materials. The method uses latitude and longitude RGB light sources for illumination, which can form distinct and different forms of rainbow bars on various types of weld defects, providing powerful conditions for defect recognition. Unlike laser structured light vision, this method fully utilizes the specular reflection characteristics of the material surface and has a faster detection speed. This article uses a ball model to reveal the decoupled correspondence between material surface color and gradient direction and magnitude under latitude-distributed and longitude-distributed RGB light source illumination, explaining the mechanism and reliability of the detection method, and providing conditions for further quantification of defects. Finally, this article combines U-Net network and its various improved versions to achieve high-precision welding defect detection, with an average accuracy of 89.88% and a recall rate of 92%.