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News of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences, 2024 Volume 26, Issue 2, Pages 44–52 (Mi izkab854)

Computer science and information processes

Computer processing of IR spectroscopy data of lubricant oils in the Table Curve 2d program

A. S. Kuznetsov, N. Yu. Razyapova, S. V. Razlivinskaya

Russian State Social University, Moscow

Abstract: This scientific article examines in detail issues related to computer processing and interpretation of the results of IR spectroscopy of lubricating oils. The experimental data obtained during the recording of spectral graphic characteristics of lubricating oils were subjected to further digitization and computer processing to reduce the noise level of the signals and create a mathematical description. A formalized description of the experimental data of IR spectroscopy has been created based on mathematical models that are nonlinear with respect to the parameters, based on the processes of their structural and parametric identification and the consistent synthesis of quantitative relationships between intensity and wave number. Using the modern software package Table Curve 2d, computer processing of experimental data and their visualization was carried out. The main quantitative criteria for the quality of mathematical models are calculated: standard error, Fisher criterion, coefficient of determination R2 . The calculated quality criteria are summarized in tables. Next, the models were ranked according to the calculated values of the quality criteria. The coefficient of determination R2 was used as the main quantitative ranking indicator. Visualization of experimental data and models of their formalization was performed. The results of calculation of the main statistical indicators, including the values of confidence intervals, are presented. The main quantitative indicators of interpretation of IR spectral data are considered. A “synthesis” and computer visualization of a differential curve characterizing the rate of the process was carried out. This indicator can be considered as an additional aspect of the quantitative interpretation of IR spectrograms of lubricating oils. The scientific research methodology is based on the analysis of scientific data, comparative analysis, data synthesis, and graphic interpretation. The result of this research is the creation of a formalized description of IR spectroscopy of lubricating oils based on nonlinear mathematical models obtained through the use of computer methods for processing IR spectra and modern software products. The work also identifies development prospects and reviews research in this area.

Keywords: computer processing, IR spectrum, lubricat oils, software product, mathematical model, mathematical description

UDC: 004.94

MSC: Primary 00A72; Secondary 93E24

Received: 05.03.2024
Revised: 18.03.2024
Accepted: 20.03.2024

DOI: 10.35330/1991-6639-2024-26-2-44-52



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© Steklov Math. Inst. of RAS, 2024