中红外光谱技术对乙醇汽油乙醇含量的检测

欧阳爱国; 张宇; 程梦杰; 王海阳; 刘燕德

doi:10.3788/CO.20171006.0752

Volume 10 Issue 6

Dec. 2017

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Chinese Optics > 2017 > 10(6): 752-759.

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): 752-759. doi: 10.3788/CO.20171006.0752

Citation:

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): 752-759. doi: 10.3788/CO.20171006.0752

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Determination of the content of ethanol in ethanol gasoline using mid-infrared spectroscopy

doi: 10.3788/CO.20171006.0752

Institute of Optics-Mechanics-Electronics Technology and Application(OMETA), East China Jiao tong University, Nanchang 330013, China

Funds:

National Natural Science Foundation of China 61640417

Collaborative Innovation Center of Jiangxi Province gjgz[2014]60

More Information

Corresponding author: LIU Yan-de, E-mail:jxliuyd@163.com
Received Date: 11 Jun 2017
Rev Recd Date: 13 Aug 2017
Publish Date: 01 Dec 2017

Abstract

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 0.958, RMSEP is 1.479%(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.

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References(18)

References

[1]	苏会波, 林海龙, 李凡, 等.乙醇汽油对减少机动车污染排放的机理研究与分析[J].环境工程学报, 2015, 9(2):823-829. doi: 10.12030/j.cjee.20150252 SU H B, LIN H L, LI F, et al.. Mechanism study and analysis on emission reduction of pollutants with ethanol gasoline[J]. Chinese J. Environment Engineering, 2015, 9(2):823-829.(in Chinese) doi: 10.12030/j.cjee.20150252
[2]	冯亦立.乙醇汽油与普通汽油的环保性比较[J].环境科技, 2009, 22(S1):124-127. http://www.doc88.com/p-73642370237.html FENG Y L. The environment characters compared between alcohols petrol and petrol[J]. Environmental Science and Technology, 2009, 22(S1):124-127.(in Chinese) http://www.doc88.com/p-73642370237.html
[3]	郭瑞莲, 鲍晓峰, 岳欣, 等.车用乙醇汽油对发动机进气系统沉积物的影响[J].汽车工程, 2007, 29(8):642-644+691. doi: 10.3321/j.issn:1000-680x.2007.08.002 GUO R L, BAO X F, YUE X, et al.. The influence of ethanol gasoline on deposit formation in intake system of the engine[J]. Automotive Engineering, 2007, 29(8):642-644+691.(in Chinese) doi: 10.3321/j.issn:1000-680x.2007.08.002
[4]	康建爽, 张璐妮, 蒋书波, 等.基于拉曼分析技术乙醇汽油辛烷值快速测定研究[J].化工自动化及仪表, 2010, 37(3):52-54. http://www.wenkuxiazai.com/doc/42f68547ad02de80d4d840d6.html KANG J SH, ZHANG L N, JIANG SH B, et al.. Rapid determination of octane number about ethanol gasoline based on Raman analysis technique[J]. Control and Instruments in Chemical Industry, 2010, 37(3):52-54.(in Chinese) http://www.wenkuxiazai.com/doc/42f68547ad02de80d4d840d6.html
[5]	CORSETTI S, ZEHENTBAUER F M, MCGLOIN D, et al.. Characterization of gasoline/ethanol blends by infrared and excess infrared spectroscopy[J]. Fuel, 2014, 141:136-142. http://www.sciencedirect.com/science/article/pii/S0016236114010205
[6]	陈彬, 武宏阳, 张贤明, 等.含微水绝缘油表面张力的中红外光谱检测[J].光学精密工程, 2015, 23(9):2452-2458. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=gxjm201509004&dbname=CJFD&dbcode=CJFQ CHEN B, WU H Y, ZHANG X M, et al.. Detection on interfacial tension of insulating oil with trace water based on mid-infrared spectroscopy[J]. Opt. Precision Eng., 2015, 23(9):2452-2458.(in Chinese) http://kns.cnki.net/KCMS/detail/detail.aspx?filename=gxjm201509004&dbname=CJFD&dbcode=CJFQ
[7]	SEN I, OZTURK B, TOKATLI F, et al.. Combination of visible and mid-infrared spectra for the prediction of chemical parameters of wines[J]. Talanta, 2016, 161:130-137. doi: 10.1016/j.talanta.2016.08.057
[8]	HU N P, WU D, CROSS K J, et al.. Structural basis of the H-1-nuclear magnetic resonance spectra of ethanol-water solutions based on multivariate curve resolution analysis of mid-infrared spectra[J]. Applied Spectroscopy, 2010, 64(3):337-342. doi: 10.1366/000370210790918373
[9]	GUIMARAES E, GONTIJO L C, MITSUTAKE H, et al.. Quantification of ethanol in biodiesels using mid-infrared spectroscopy and multivariate calibration[J]. Industrial & Engineering Chemistry Research, 2014, 53(35):13575-13580. doi: 10.1021/ie502067h
[10]	ZHOU S, HAN Y L, LI B C. Simultaneous detection of ethanol, ether and acetone by mid-infrared cavity ring-down spectroscopy at 3.8μm[J]. Applied Physics B, 2016, 122(7):187. doi: 10.1007/s00340-016-6465-1
[11]	ZHENG W B, FU X P, YING Y B. Spectroscopy-based food classification with extreme learning machine[J]. Chemometrics and Intelligent Laboratory Systems, 2014, 139:42-47. doi: 10.1016/j.chemolab.2014.09.015
[12]	YANG L M, ZHANG S Y. A sparse extreme learning machine framework by continuous optimization algorithms and its application in pattern recognition[J]. Engineering Applications of Artificial Intelligence, 2016, 53:176-189. doi: 10.1016/j.engappai.2016.04.003
[13]	LI S, DAI L K. Classification of gasoline brand and origin by Raman spectroscopy and a novel R-weighted LSSVM algorithm[J]. Fuel, 2012, 96(7):146-152. http://www.sciencedirect.com/science/article/pii/S0016236112000075
[14]	冯愈钦, 吴龙国, 何建国, 等.基于高光谱成像技术的长枣不同保藏温度的可溶性固形物含量检测方法[J].发光学报, 2016, 37(8):1014-1022. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=fgxb201608019&dbname=CJFD&dbcode=CJFQ FENG Y Q, WU L G, HE J G, et al.. Detection method of soluble solid of jujube at different preservative temperature based on hyper-spectral imaging technology[J]. Chinese J. Luminescence, 2016, 37(8):1014-1022.(in Chinese) http://kns.cnki.net/KCMS/detail/detail.aspx?filename=fgxb201608019&dbname=CJFD&dbcode=CJFQ
[15]	刘燕德, 靳昙昙, 王海阳.基于拉曼光谱的三组分食用调和油快速定量检测[J].光学精密工程, 2015, 23(9):2490-2496. http://kns.cnki.net/KCMS/detail/detail.aspx?filename=gxjm201509009&dbname=CJFD&dbcode=CJFQ LIU Y D, JIN T T, WANG H Y, et al.. Rapid quantitative determination of components in ternary blended edible oil based on Raman spectroscopy[J]. Opt. Precision Eng., 2015, 23(9):2490-2496.(in Chinese) http://kns.cnki.net/KCMS/detail/detail.aspx?filename=gxjm201509009&dbname=CJFD&dbcode=CJFQ
[16]	洪茜, 刘木华, 袁海超, 等.基于表面增强拉曼光谱的鸭肉中螺旋霉素残留检测[J].发光学报, 2015, 36(12):1464-1468. http://www.opticsjournal.net/abstract.htm?id=OJ150120000013SoUrXu HONG Q, LIU M H, YUAN H CH, et al.. Detection of spiramycin residue in duck meat based on SERS[J]. Chinese J. Luminescence, 2015, 36(12):1464-1468.(in Chinese) http://www.opticsjournal.net/abstract.htm?id=OJ150120000013SoUrXu
[17]	陈云坪, 马伟, 王秀, 等.基于PLS的土壤养分与小麦产量空间相关关系研究[J].农业机械学报, 2012, 2:159-164. doi: 10.6041/j.issn.1000-1298.2012.02.031 CHEN Y P, MA W, WANG X, et al.. Study on the correlation between yield and soil nutrients PLS space wheat[J]. Transactions of the Chinese Society of Agricultural Machinery, 2012, 2:159-164.(in Chinese) doi: 10.6041/j.issn.1000-1298.2012.02.031
[18]	BITTANTE G, CECCHINATO A. Genetic analysis of the Fourier-transform infrared spectra of bovine milk with emphasis on individual wavelengths related to specific chemical bonds[J]. J. Dairy Science, 2013, 96(9):5991 http://www.ncbi.nlm.nih.gov/pubmed/23810593