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Quantitative Analysis of Fuel Blends Based on Raman and Near Infrared Absorption Spectroscopy |
LIU Zhe1, LUO Ning-ning2, SHI Jiu-lin1, 2 *, ZHANG Yu-bao2, HE Xing-dao1, 2 |
1. Jiangxi Engineering Laboratory for Optoelectronics Testing Technology, Nanchang Hangkong University, Nanchang 330063, China
2. Key Laboratory of Nondestructive Test (Ministry of Education), Nanchang Hangkong University, Nanchang 330063, China |
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Abstract Biodiesel is a typical “green energy” with good environmental protection and fuel characteristics. It is usually mixed with diesel to use in diesel engines. However, there is no uniform standard for the blend proportion of diesel and biodiesel at present, and different proportions of diesel/biodiesel blend present different combustion performance, which also have a certain impact on diesel engines. In order to measure the concentration of biodiesel in diesel/biodiesel blend quickly and accurately, near infrared spectroscopy (NIR) and Raman spectroscopy have been used in fuel detection. In this paper, the concentration of biodiesel in diesel/biodiesel blends was quantitatively analyzed by using Raman spectroscopy combined with NIR. The Raman spectra and NIRs of diesel/biodiesel blends were measured firstly, and then the spectra were pre-processed by smoothing, baseline correction and normalization. The Raman and NIRs of diesel/biodiesel blend present C═O characteristic spectral regions, and show corresponding trends with the increase of biodiesel concentration. The main variation of C═O characteristic region with biodiesel concentration in Raman spectra is the characteristic peak at 1 743 cm-1, while the main variation of C═O characteristic region with biodiesel concentration in NIRs is the characteristic peak at 4 659 cm-1. Afterwards, the concentration prediction models of biodiesel in mixed fuel based on the strength ratio method and partial least squares (PLS) regression method were established respectively. When using intensity ratio method to establish the biodiesel concentration prediction model in the characteristic peak, the correlation coefficients of C═O characteristic peak linear prediction model established by Raman spectroscopy and near infrared spectroscopy were 0.947 2 and 0.996 2, respectively. When using partial least squares (PLS) regression method to establish the biodiesel concentration prediction model in the characteristic spectral region, the correlation coefficients (R2) of the prediction set established from the Raman and near infrared spectral characteristic regions of the blended fuel are 0.981 5 and 0.991 2 respectively, and the corresponding RMSE are 0.093 7 and 0.012 9 respectively. The results show that the biodiesel concentration prediction model based on the C═O spectral region in near infrared spectroscopy can obtain more accurate prediction results in mixed fuel.
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Received: 2019-04-18
Accepted: 2019-09-20
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Corresponding Authors:
SHI Jiu-lin
E-mail: jiulinshi@126.com
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