[Developing near infrared spectroscopy calibration model of molar ratio between methanol and isobutylene by support...

In petrochemical industries, the molar ratio between methanol and isobutylene is one of the most important control parameters in methyl tertiary butyl ether (MTBE) production plant. However, traditional on-line gas chromatography method is difficult to use in practice because of its high maintenance and low speed. On-line near infrared spectroscopy is hopeful to become an excellent alternative method for determining the parameter due to its rapidness, convenience, and less maintenance. Because of the nonlinearity of the measured parameter and near infrared spectra, support vector regression, a novel powerful nonlinear calibration method, was used to build calibration model in the present paper. Compared with the results of partial least squares (PLS) and artificial neural network (ANN) method, the prediction accuracy of support vector regression model is high enough to meet the demand for process control of MTBE unit. This calibration method can be applied to real online analysis of the molar ratio between methanol and isobutylene by near infrared spectroscopy.