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| Qualitative Discrimination and Quantitative Determination Model Research of Methanol Gasoline and Ethanol Gasoline |
| HU Jun, LIU Yan-de*, HAO Yong, SUN Xu-dong, OUYANG Ai-guo |
| School of Vehicle and Mechatronics Engineering, East China Jiaotong University, Nanchang 330013, China |
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Abstract Methanol gasoline and ethanol gasoline are both clean energy sources, but the advantages and disadvantages of them are different. Among them, the content of methanol or ethanol determines the performance of gasoline. Therefore, it is of great significance to qualitatively distinguish methanol gasoline and ethanol gasoline and quantitatively determine the alcohol content in alcohol gasoline. In this paper, the types of alcohol gasoline and its content were identified and quantitatively analyzed by mid-infrared spectroscopy. Firstly, by comparing and analyzing the mid-infrared spectroscopy of methanol gasoline and ethanol gasoline, Random Forest (RF) was used to discriminate methanol gasoline and ethanol gasoline samples. After establishing the qualitative model of methanol gasoline and ethanol gasoline, the quantitative determination model of methanol gasoline and ethanol gasoline is established to accurately determine the corresponding alcohol content in gasoline. In order to reduce the spectrum drift and light scattering caused by vibration and noise of the experimental instrument during the experiment, the mid-infrared spectrum was pretreated. In the process of analysis, different pre-treatment methods are first used for correction, such as S-G convolution smoothing, Multivariate Scattering Correction (MSC), Standard Normal Variable (SNV), derivatives (1st derivative and 2nd derivative), and then, Least Square Support Vector Machine (LSSVM) models of methanol gasoline and ethanol gasoline were established respectively. It was found that the discriminant accuracy is up to 98.23% when the number of decision trees was 61. Secondly, for the LS-SVM model, the comparison of modeling results showed that for both methanol gasoline and ethanol gasoline, SNV pre-treatment had the best effect. The predictive correlation coefficient Rp of LSSVM model after the transformation of standard normal variables for methanol content determination of methanol gasoline was 0.951 9 and RMSEP was 1.766 3. In the same situation, ethanol gasoline was 0.951 5 and 1.770 3, respectively. This research can provide technical reference and theoretical basis for the qualitative discrimination and content determination of methanol gasoline and ethanol gasoline. The detection technology can provide a new method for the measurement of alcohol gasoline in the methanol gasoline industry, which has important practical significance and lays a foundation for the detection of other types of chemical products.
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Received: 2019-06-25
Accepted: 2019-10-30
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Corresponding Authors:
LIU Yan-de
E-mail: jxliuyd@163.com
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