Multivariate Analysis-Based Laser-Induced Breakdown Spectroscopy for Monitoring of Laser Paint Cleaning

In this study, a high-power Nd:YAG laser was used to remove a thick paint coating layer from 304L stainless steel (SS304L). Different numbers of laser paint cleaning processes were performed, and an electron probe micro analyzer (EPMA) analysis was used to examine the SS304L surface condition. The surface elemental distributions of SS304L were strongly dependent on the laser paint cleaning process owing to the different levels of paint removal. Laser-induced breakdown spectroscopy (LIBS) was also adopted to monitor the laser paint cleaning process. Two different types of LIBS-based 2-dimension (2D) mapping were developed. 2D elemental distribution maps were constructed using the LIBS peak intensities of Fe (374.95 nm) Cr (520.84 nm), and Na (588.99 nm). Moreover, 2D correlation coefficient distribution maps were constructed using the Pearson’s correlation coefficient. These two different 2D mappings were compared with the elemental distribution maps obtained from the EPMA analysis, and the latter shows excellent agreement with the EPMA analysis. This study presents the possibility of the LIBS-based monitoring for the laser paint-cleaning process using multivariate correlation analysis.