Determination of Gasoline Composition Based on Raman Spectroscopy

For the purpose of the rapid prediction of every composition in gasoline, the Raman spectra of the gasoline brand 93 and 97, a batch of one-one mixtures with aromatic, olefin, ben, methanol and ethanol with different ratios are measured, 410 mixture samples were measured totally in this research. The obtained Raman spectra were preprocessed by a series of processing, they were data smoothing, baseline deduction and spectral normalized, etc. After that 33 characteristic peaks were extracted to be the eigenvalues for the whole Raman spectra. According to the current national standard test method, the values of every composition were measured by the gas chromatography. By using the eigenvalues as inputs, and actual contents of aromatic, olefin, ben, methanol and ethanol got from gas chromatography as outputs, two mathematical models of multi-output least squares support vector regression and partial least squares combination with multiple regression analysis were established to predict the values of the above compositions of a sample, respectively. The predicting results were compared with the values calculated from the gas chromatography measurement results and the mixture proportions, the multi-output least squares support vector regression has a better effects, and the obtained root mean square error of prediction for aromatic, olefin, ben, methanol and ethanol are 0.27%, 0.27%, 0.22%, 0.17%, 0.14%; the correlation coefficients are 0.999 3, 0.998 5, 0.998 6, 0.992 3, 0.993 5, respectively. This model is also applied to the detection of the unknown sample, the root mean square error of the prediction for the results does not exceed 0.5%, which can achieve the measurement requirements in the industry. Results show that the Raman spectra analysis technology based on multi-output least squares support vector regression can be a precise, fast and convenient new method for gasoline composition detection, and can be applied to the quality control of the gasoline production process, transportation, storage of the gasoline.