Oil Condition Monitoring based on Chemometric Evaluation of Spectroscopic Analysis Data

摘要

Increasing costs as well as environmental aspects demand a spare use of lubricating fluids. Used oil analyses has thus developed as a reliable tool for both, oil condition and wear state assessment during the past decades. Oil ageing, however, is a complex process including base oil degradation, additive depletion and contamination. Diverse analytical procedures have to be performed for a comprehensive evaluation of oil condition. The application of these methods is connected to an intensive use of solvents and chemicals or at least time- and labour-intensive. Moreover, certain well-established analytical techniques don't apply to the entire range of modern base oils, additive packages or fuel compositions. Infrared spectroscopy is one of the common methods in used oil analyses, for example for oxidation measurement. But even if complete spectra are recorded, only a small fraction of the information is used for oil condition rating. All active standards correlate discrete absorption bands to single chemical properties. The spectra, however, reflect the entire change in oil composition in relation to the fresh oil. This talk presents the extraction of this information using a statistical approach. Based on a training data set, a chemometric model is built and used to predict classical wet-chemical parameters like acid number, base number or water content.