Determining the presence of naphthenic and vegetable oils in paraffin-based lubricant oils using near infrared spectroscopy and support vector machines

Abstract

The presence of naphthenic base oil and/or vegetable oil in paraffin-based lubricant oils such as automotive engine lubricant oils can severely compromise the lubricant properties and this can cause serious engine damage. A simple and fast method to identify such base stocks in mixture with paraffinic base oil and automotive engine lubricant oil is of great interest for quality monitoring. Near infrared (NIR) spectroscopy combined with chemometric methods has been applied for the development of efficient analytical methods for complex mixtures such as the ones that occur in petroleum derivatives. In this work, we carried out a study to develop classification models using support vector machines (SVM) applied to near infrared (NIR) spectroscopy data to determine the presence of naphthenic oil and/or vegetable oil in paraffin-based oils such as base oil and engine lubricant oil and the results were compared with those obtained with soft independent modeling of class analogy (SIMCA). The use of near infrared (NIR) spectroscopy and SVM provides the greatest results and a fast and simple method that achieves 95% and 100% of right predictions in the validation sample set and 87% and 75% of right predictions in the prediction sample set for the identification of naphthenic base oil, as well as for simultaneous identification of naphthenic base oil and vegetable oil in paraffin-based oils.