Acta Univ. Agric. Silvic. Mendelianae Brun. 2017, 65(3), 933-938 | DOI: 10.11118/actaun201765030933

Application of FTIR Spectrometry Using Multivariate Analysis for Prediction Fuel in Engine Oil

Marie Sejkorová
Department of Transport Means and Diagnostics, Jan Perner Transport Faculty, University of Pardubice, Studentská 95, 532 10 Pardubice, Czech Republic

This work presents the potentiality of partial least squares (PLS) regression associated with Fourier transform infrared spectroscopy (FTIR spectrometry) for detecting penetration of diesel fuel into the mineral engine oil SAE 15W-40 in the concentration range from 0 % to 9.5 % (w/w).
As a best practice has proven FTIR-PLS model, which uses the data file in the spectral range 835-688 cm-1.The quality of the model was evaluated using the root mean square error of calibration (RMSEC) and cross validation (RMSECV). A correlation coefficient R = 0.999 and values of RMSEC, RMSECV were obtained 0.11 % and 0.38 % respectively. After the calibration of the FTIR spectrometer, the contamination engine oil with diesel fuel could be obtained in 1-2 min per sample.

Keywords: engine oil, FTIR spectrometry, multivariate analysis, lubricant analysis, lubricant quality, diesel fuel, partial least squares (PLS) regression

Prepublished online: July 3, 2017; Published: May 1, 2017  Show citation

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Sejkorová, M. (2017). Application of FTIR Spectrometry Using Multivariate Analysis for Prediction Fuel in Engine Oil. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 65(3), 933-938. doi: 10.11118/actaun201765030933
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