Title :
Determination of Olefin Hydrocarbons in Gasoline by Partial Least-Squares
Author :
Jun, Gao ; Yandong, Song ; Jibin, Ding ; Bo, Zheng ; Jiangtao, Xu
Author_Institution :
Binjiang Coll., Nanjing Univ. of Inf. Sci. &Technol., Nanjing, China
Abstract :
By using near-infrared technology, a method is presented to determine the alkenes content in gasoline. There are 30 gasoline samples to be used as trained set for building calibration model and their alkenes hydrocarbons content is determined by GC. In the region of 1000-2000nm, the near-infrared spectroscopy is optimized by Fourier transformation. According to the optimized data, the cross validated and partial least-squares regression is performed to establish the model. In training set, the average error and square correlation coefficient is 0.2% and 0.9881, average error in test set was 0.39, which shows good correlation and predictability.
Keywords :
chromatography; infrared spectroscopy; least squares approximations; organic compounds; petroleum; regression analysis; GC; alkene hydrocarbons; gas chromatography; gasoline; near infrared technology; olefin hydrocarbons; partial least square regression; square correlation coefficient; wavelength 1000 nm to 2000 nm; Automation; Calibration; Computer industry; Educational institutions; Gas industry; Hydrocarbons; Mechanical engineering; Petroleum; Spectroscopy; Testing; gasoline; near-infrared spectrum; olefin hydrocarbons; partial least-squares regression;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.728
