Abstract
Based on near-infrared (NIR) spectroscopy and Monte Carlo virtual spectrum identification method, a fast analytical tool is presented for rapid prediction of key gasoline properties; 542 reformed gasoline samples were collected to establish NIR spectroscopic database for determination of research octane number and hydrocarbon groups. The prediction accuracy of the Monte Carlo method is slightly lower than that of PLS, but the method does not need modeling and model maintenance, the results show that the standard deviation of prediction of paraffin, isoparaffin, olefins, aromatics, naphthenes, and octane number are 0.31%, 0.47%, 0.21%, 0.43%, 0.67% and 0.25, respectively, which meet the requirements of fast assessment. This method can significantly reduce the maintenance of traditional multivariate calibration.
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