The C, Mn, Si, Cr, Ni, and Cu concentrations were calibrated from low-resolution laser-induced breakdown spectra of low-alloy steel reference standards. Multivariate calibration models for all considered elements were built based on data preprocessing in the form of normalizing spectra to the Fe II 252.0609-nm emission line and baseline correction in addition to selection of spectral variables using an original method of searching a combination of moving windows for a partial least-squares method. The characteristics of the models were a root-mean-square error and residual predictive deviation (RPD) of 0.04% and 4.7 for C (at concentrations up to 0.7%); 0.02% and 24.8 for Mn (up to 1.9%); 0.01% and 12.9 for Si (up to 0.9%); 0.01% and 21.8 for Cr (up to 1%); 0.007% and 23.3 for Ni (up to 0.7%); 0.006% and 23.2 for Cu (up to 0.5%), respectively. The models were quantitative (RPD > 3) for the six considered elements including C.
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Translated from Zhurnal Prikladnoi Spektroskopii, Vol. 90, No. 2, pp. 174–179, March–April, 2023. https://doi.org/10.47612/0514-7506-2023-90-2-174-179.
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Belkov, M.V., Catsalap, K.Y., Korolko, D.A. et al. Multivariate Calibration of the Composition of Low-Alloy Steels Using Preprocessed Low-Resolution Emission Spectra with Spectral Variables Selection. J Appl Spectrosc 90, 274–278 (2023). https://doi.org/10.1007/s10812-023-01532-8
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DOI: https://doi.org/10.1007/s10812-023-01532-8