Application of FTIR-ATR Spectrometry in Conjunction with Multivariate Regression Methods for Viscosity Prediction of Worn-Out Motor Oils

Abstract

Viscosity is considered to be a key factor in the quality of lubrication by oil and engine manufacturers and is therefore one of the most monitored parameters of lubricants. FTIR (Fourier-transform infrared) spectrometry in combination with Partial Least Squares (PLS) and Principal Component Regression (PCR) was therefore proposed and tested as an alternative to the standardized method for determining the kinematic viscosity at 100 °C with an Ubbelohde capillary viscometer (CSN EN ISO 3104) of worn-out motor oil grade SAE 15W-40. The FTIR-PLS model in the spectral region of 1750–650 cm−1 with modification of the spectra by the second derivative proved to be the most suitable. A significant dependence of R = 0.95 was achieved between the viscosity values of 190 samples of worn-out motor oils, which were determined by a standardized laboratory method, and the values predicted by the FTIR-PLS model. The Root Mean Square Error of Calibration (RMSEC) parameter reached 0.148 mm2s−1 and the Root Mean Square Error of Prediction (RMSEP) parameter reached 0.190 mm2s−1. The proposed method for determining the kinematic viscosity at 100 °C by the FTIR-PLS model is faster compared to the determination according to the CSN EN ISO 3104 standard, requires a smaller amount of oil sample for analysis and produces less waste chemicals.

Keywords

• oil condition monitoring (OCM)
• motor oil
• lubricants
• FTIR spectrometry
• kinematic viscosity
• Partial Least Squares (PLS) regression