中国光学, 2017, 10 (6): 752, 网络出版: 2017-12-25
中红外光谱技术对乙醇汽油乙醇含量的检测
Determination of the content of ethanol in ethanol gasoline using mid-infrared spectroscopy
中红外光谱 乙醇汽油 极限学习机 最小二乘支持向量机 偏最小二乘 mid infrared spectroscopy(MIRS) ethanol gasoline extreme learning mathine(ELM) least squares support vector machine(LSSVM) partial least squares(PLS)
摘要
乙醇汽油是一种新型清洁燃料, 燃料乙醇在乙醇汽油中的含量会影响发动机的性能。为了确保发动机的工作可靠性, 需要对乙醇汽油中的乙醇含量进行快速精准检测。本文使用中红外光谱技术对采集到的乙醇汽油的光谱数据进行定量分析。首先对原始光谱数据使用多元散射校正、基线校正、一阶导数、二阶导数等预处理方法进行预处理。然后利用ELM、LSSVM、PLS对乙醇汽油中的乙醇含量建立预测模型, 通过比较3种建模方法对乙醇含量的预测能力发现, PLS方法的精度比其余两种方法更高。模型决定因子R2为0958, 预测均方误差RMSEP为1479%(V/V,体积比)。中红外光谱技术对乙醇汽油乙醇含量的快速准确检测提供了新的思路。
Abstract
Ethanol gasoline is a new type of clean fuel, and the content of fuel ethanol in ethanol gasoline affects the performance of the engine. In order to ensure the reliability of engine operation, the ethanol content of ethanol gasoline should be detected quickly and accurately. This paper uses mid-infrared spectroscopy to quantitatively analyze the collected spectral data of ethanol gasoline. First, the original spectral data were preprocessed using multiple scattering correction(MSC), baseline correction, first derivative, second derivative and other pretreatment methods. Then, the predictive model of ethanol content in ethanol gasoline is established using ELM, LSSVM and PLS. By comparing the predictive ability of the three modeling methods, it is found that the accuracy of PLS method is higher than the other two methods. The model determination factor R2 is 0958, RMSEP is 1479%(V/V, volume ratio). The mid-infrared spectroscopy provides a new idea for the rapid and accurate detection of ethanol content of in ethanol gasoline.
欧阳爱国, 张宇, 程梦杰, 王海阳, 刘燕德. 中红外光谱技术对乙醇汽油乙醇含量的检测[J]. 中国光学, 2017, 10(6): 752. OUYANG Ai-guo, ZHANG Yu, CHENG Meng-jie, WANG Hai-yang, LIU Yan-de. Determination of the content of ethanol in ethanol gasoline using mid-infrared spectroscopy[J]. Chinese Optics, 2017, 10(6): 752.