Determination Of Gasoline Octane Number Using Raman Spectroscopy

Some properties of petroleum products such as gasoline octane number are necessary to be analyzed regularly. Traditional laboratory analysis methods are usually not suitable because of their cost, long delay, complication of operation and maintenance. Raman spectroscopy is a non-destructive and rapid analysis method, which is preferable to rapidly determine the properties of petroleum products offline or online. This thesis researched the application techniques of Raman spectroscopy and developed a new gasoline octane number analyzer using Raman spectroscopy. The main contributions of this thesis are as follows:1. Introduce the principles of Raman spectroscopy, and then review the application of Raman spectroscopy in petroleum products analysis.2. Apply wavelet transform in the pre-processing of gasoline Raman spectra in order to reduce the fluorescence backgrounds and to improve the signal-to-noise ratio of the spectra. Experimental results show that the application of wavelet transform obviously improves the prediction performance of Partial Least Squares (PLS) model for research octane number (RON) and motor octane number (MON), comparing with regular pretreatment methods.3. To overcome the disadvantages of linear calibration methods such as PLS, least squares support vector machine (LS-SVM) is introduced to the quantitative calibration of gasoline using Raman spectroscopy. Besides, a novel adaptive modeling technique is proposed in order to meet the practical need of rapid determination of gasoline octane number. For a set of commercial gasoline samples, the LS-SVM model obtains better performance than the PLS model on the prediction of RON.4. Based on the above research results, a gasoline octane number analyzer using Raman spectroscopy has been developed. For a set of gasoline samples, the analyzer performs satisfactorily on the prediction of RON and MON.