Abstract
Three-dimensional (3D) distribution of elements on the sample surface is very important for materials analysis. With its micro-damage characteristic, laser-induced breakdown spectroscopy (LIBS) has the potential to realize 3D distribution analysis of elements on the material surface. In this work, we investigated a method of image-assisted laser-induced breakdown spectroscopy (IA-LIBS) to monitor the ablation process. The changing trends of spectral intensities, ablation crater parameters and plasma image features with the number of pulses have been analysed. To obtain the best prediction accuracy for the average depth of ablation crater, a partial least square regression (PLSR) prediction model was established by using the features of gray-gradient co-occurrence matrix (GGCM) in plasma images. The coefficient of determination (R2) of the model was 0.954, the root-mean-square error of cross-validation (RMSECV) was 7.535, and the root-mean-square error of prediction (RMSEP) was 7.442. Finally, 3D distribution analysis of Mg and Fe elements on the surface of 5052 aluminum alloy was realized. The experimental results indicate that IA-LIBS can effectively monitor the ablation process.
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