Detection of ethanol content in ethanol diesel based on PLS and Multispectral method

Abstract Ultraviolet spectroscopy (UV) and near-infrared (NIR) spectroscopy combined with Partial Least Square (PLS) was used as a destructive technique to detect the ethanol content in ethanol diesel mixture. The spectral data were obtained by ultraviolet (TU-1901/1900) and near infrared spectroscopy (IRTracer-100). The Savitaky-Golay (S-G) method and Max-min normalization method were used to pretreat and normalize the spectral data, respectively. Then the regression models were established by the pretreated spectral data of UV, NIR and UV-NIR combined with PLS, and the evaluation parameters including r c , r p , RMSECV and RMSEP were used to compare the results of three regression models. The results show that the evaluation parameters of the UV-NIR fusion spectrum are r p =1, RMSECP =0.00156, r c =0.8431 and RMSEV =0.0148, respectively. Compared with the evaluation parameters of the UV and the NIR spectrum, the RMSECP is reduced by 0.00169 and 0.01224, and the r c is increased by 0.0902 and 0.1813, respectively. These results indicated that the regression model of the UV-NIR fusion spectrum has more accuracy than that of the single spectrum, and the regression model established by UV-NIR fusion spectrum combined with PLS can detect the ethanol content.