In this paper, a scanning laser system based on an array couple charged detector (CCD) has been developed to detect and measure quantitatively the morphology and depth of defects on continuously cast billet (CC billet) surface at high temperatures. The technique, based on a linear light scattering method, employs a low power He-Ne laser and a conventional CCD probe and enables a narrow line array laser beam to be projected on the test surface across the width direction on the CC billet surface. In the relative scanning direction between the test surface and the CCD probe, the one-dimensional linear surface image acquired by the CCD sensor at a given shutter time, which exhibits the curvature change of the laser scanning line, can be used to determine the distance morphology according to triangulation principles. Combining with casting speed, a linear laser beam image can be spliced into a two-dimensional surface image that constructs the billet surface profile and detects surface defect shape and depth. Furthermore, it can reconstruct a threedimensional morphology for the billet surface defects in the high temperature condition. Proof of concept experiments have been performed through online measurement of different size defects, and quality tracking on the hot CC billet surface has been implemented.

Various methods of detecting surface defects are being used in automated industrial manufacturing environments. This work presents the design and development of a laser charged couple device (CCD) displacement scanning system. The surface defect detection method using a laser CCD displacement sensor is derived from an idea in which surface defects such as cracks, inclusions and holes of three-dimensional morphology characteristics are compared to normal surface especially in continuous casting slabs. Some novel research methods have been applied to develop the surface defect detection system used: first, getting a one-dimensional distance matrix along transverse direction and a two-dimensional matrix combining with a certain moving speed through the laser CCD displacement sensor; second, obtaining the slab surface profile and mapping to a greyscale image and finally, obtaining the surface defect regions by an image processing and searching algorithm and quantitatively detecting slab surface defect shape and depth. The research results in the lab trials have shown that the methodology proposed is effective to detect two-dimensional defect size and reconstruct a three-dimensional surface defect shape. At the same time, it is also able to accurately locate and identify surface defects and realise automatic surface defect non-destructive detection online, and provides a theoretical base and technology idea for further studying surface defects online inspection for hot continuous casting slab.