During high power disk laser welding, the high-speed photography was used to measure the dynamic images of the laser-induced plume at different laser welding speeds. Various plume features （area, height and brightness） were extracted from the images by the color space clustering algorithm. Combined with observation on the surface and the cross sections of welding samples, the effect of welding speed on welding stability was analyzed. From the experimental results, it was found that these features of plume could reflect the welding state. Thus changes of the plume features corresponded to different welding speeds, which was helpful for monitoring the laser welding stability.
High-speed photography was used to obtain the dynamic changes in the surface plasma during a high-power disk laser welding process. A color space clustering algorithm to extract the edge information of the surface plasma region was developed in order to improve the accuracy of image processing. With a comparative analysis of the plasma features, i.e., area and height, and the characteristics of the welded seam, the relationship between the surface plasma and the stability of the laser welding process was characterized, which provides a basic understanding for the real-time monitoring of laser welding.
