Preprocessing of Laser-Induced Breakdown Spectra of Low Alloy Steels and Cast Irons Using Partial Least-Squares Regression Analysis

Regression models for the analysis of manganese, chromium, nickel, copper, silicon, vanadium, titanium, and aluminum were constructed using partial least-squares regression based on a set of laser-induced breakdown spectra of low-alloy steels. The spectra were recorded in the range 288–325 nm with a resolution of ~0.04 nm. The laser plasma was excited in a collinear two-pulse mode at wavelength 1064 nm. The efficiency of various methods of spectrum preprocessing (normalization to the baseline, localization of the spectral range, addition of nonlinear components of the spectrum), which allowed the accuracy of the regression models to be improved, was studied. The standard deviation of the analysis results for test samples could be improved in the range from 1.8 times for vanadium to 6.8 times for silicon if the optimal preprocessing method was used.