Study on brand identification of lubricating oil using sensitive wavelengths of visible and short-wave near infrared spectroscopy

The feasibility of visible and short-wave near-infrared spectroscopy(VIS/WNIR) techniques as means for the nondestructive and fast brand identification of lubricating oil was evaluated. And selected sensitive bands was found validated. 90 lubricating oil samples were randomly selected for the calibration set, while the remaining 90 samples for the prediction set. smoothing way of moving average and standard normal variate (SNV) were used to pretreat spectra data. Based on principal components analysis, 2-D principal components plot was clustered well. Least-squares support vector machines (LS-SVM) was applied to brand identification based on absorbance spectra from 421 nm to 1075 nm. Finally, recognition ratio of 100% was obtained. Sensitive bands, 442 and 926 nm were obtained by loading weights in partial least squares and discrimination power in principal components analysis (PCA). The prediction results of 100% indicated that the selected wavelengths reflected the main characteristics of lubricating oil of different brands based on SWNIR spectroscopy and LS-SVM model.