Plasma Spectrum Diagnosis and Cleaning Quality Analysis of Laser Cleaning of Marine Biofilms on Aluminum Alloy Surfaces

Surface quality monitoring has become increasingly important in the laser cleaning process. Currently, most research focuses on cleaning contaminants such as oxides and paints, while studies on the cleaning of marine biofilm layers from metal surfaces remain limited. This paper presents real-time monitoring of nanosecond pulsed laser cleaning of marine biofilm layers on aluminum alloy surfaces using laser-induced breakdown spectroscopy (LIBS). The plasma spectra of different microbial layers during cleaning were collected to analyze the variations in characteristic elements. Regression fitting techniques were used to analyze the evolution of plasma spectra in the long-wave band and at specific wavelengths, establishing a relationship between spectral signals and cleaning effectiveness. After cleaning, energy dispersive spectroscopy (EDS) characterization was performed on the sample surface to verify the changes in elemental composition during the cleaning process of different marine biofilm layers. Additionally, the plasma spectra corresponding to the optimal cleaning process for each microbial layer were defined as the "reference spectrum". The Pearson correlation coefficient between random spectra and the "reference spectrum" was calculated to determine the optimal cleaning process. The highest correlation results were found to predict the optimal cleaning parameters with a relative error between 0.9% and 3.8% when compared to experimentally measured values. The feasibility of LIBS technology for monitoring the laser cleaning process of marine biofilm layers on metal surfaces was validated in this study, and a theoretical foundation was provided for the future use of LIBS in enabling intelligent feedback control of the laser cleaning process.