Abstract
The use of near infrared (NIR) spectroscopy and chemometrics for the prediction of seven lubricant base oil properties was studied. The partial least-squares calibration models were developed using spectra acquired on an acousto-optic tunable filter (AOTF)-NIR spectrophotometer equipped with a fibre-optic probe in the 1100–1700 nm region. In this work, 88 samples obtained from three Brazilian refineries over a period of two years were employed. Different variable selection and sample selection methods were also investigated. The partial least squares regression (PLSR) models thus obtained showed good correlation coefficients for the properties studied and the calculated root mean square errors of prediction (relative density = 0.0005 g cm−3; molecular weight = 12 g mol−1; flash point = 7°C; temperature 50% recovered = 6.5°C; aromatic carbon assay = 0.5%; naftenic carbon assay = 1.0% and parafinic carbon assay = 1.4%) were lower than half the reproducibility values defined by the ASTM methods, except for the relative density. These results indicate, therefore, the potential of the NIR spectroscopy and chemometric techniques for on-line lubricant oil production process control.
Published Version
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