基于拉曼光谱的天然气主要组分定量分析
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摘要
经脱硫脱水处理后的天然气组分包括甲烷、乙烷、丙烷、二氧化碳、氮气、氢气、一氧化碳以及C_4以上(记为C_4~+)的未知烷烃成分等物质,其中前7种组分为天然气中的主要组分,占天然气含量的90%以上。在运用已有的拉曼光谱分析方法对天然气成分进行分析时,少量的C_4~+未知烷烃组分会对结果造成较大的影响。本研究提出了一种新的拉曼分析方法,由拉曼光谱自动分解算法和定量分析模型组成。首先,基于拉曼光谱的线型叠加性,利用非线性最小二乘法将天然气拉曼光谱分解为7种纯物质组分的拉曼光谱分量和若干个洛伦兹谱峰之和的形式,其中C_4~+未知烷烃成分的含量是用各种烷烃分子共有的CH变形振动峰反映。然后,利用训练样本来建立其它物质相对于甲烷的特征峰面积和对应的浓度之间的模型。相比于已有的拉曼分析方法,本算法克服了含有C_4~+未知烷烃成分的天然气组分的检测难题,且具有较好的稳定性和准确性。实验结果表明,此方法对甲烷、乙烷、丙烷、二氧化碳、氮气、氢气和一氧化碳的最大绝对测量误差分别为0.57%、0.37%、0.21%、0.07%、0.18%、0.04%和0.13%;与气相色谱检测结果的相关系数也分别达到了0.997、0.986、0.991、0.998、0.993、1.000、0.995和0.982。
After desulfurization and dehydration treatment,natural gas is composed of methane,ethane,propane,carbon dioxide,nitrogen,hydrogen,carbon monoxide and unknown alkane components of C4 or more( denoted as C4+). The sum of the content of first seven components is more than 90% of natural gas.When the existing Raman spectral analysis methods are applied to analyze the natural gas composition,a small amount of unknown alkane components C4+will have a greater impact on the analysis precision. On the basis of this,a novel Raman analysis method which consists of a spectral automatic decomposition algorithm and a quantitative analysis model has been developed. Based on a linear additivity of Raman spectra,the Raman spectrum of a natural gas sample can be decomposed into the sum of the Raman spectra of pure constituents and several Lorentz peaks by a nonlinear least-square optimization algorithm. The content of the unknown alkane component C4+can be described as the area of CH deformation vibration peak common for most alkane molecules. Samples of the training set are used to establish the model between Raman characteristic peak area and corresponding concentration for each component relative to methane. Compared with the existing Raman analysis methods,the new method solves the issue of analyzing natural gas containing unknown alkane components and has good stability and accuracy. Experiments show that the maximum absolute errors of this algorithm for methane, ethane, propane, carbon dioxide, nitrogen, hydrogen, and carbon monoxide respectively reach 0.57%,0.37%,0.21%,0.07%,0.18%,0.04%,0.13%,and the correlation coefficient of gas chromatographic results also reaches 0. 997,0. 986,0. 991,0. 998,0. 993,1. 000,0. 995,0. 982,respectively.
After desulfurization and dehydration treatment,natural gas is composed of methane,ethane,propane,carbon dioxide,nitrogen,hydrogen,carbon monoxide and unknown alkane components of C4 or more( denoted as C4+). The sum of the content of first seven components is more than 90% of natural gas.When the existing Raman spectral analysis methods are applied to analyze the natural gas composition,a small amount of unknown alkane components C4+will have a greater impact on the analysis precision. On the basis of this,a novel Raman analysis method which consists of a spectral automatic decomposition algorithm and a quantitative analysis model has been developed. Based on a linear additivity of Raman spectra,the Raman spectrum of a natural gas sample can be decomposed into the sum of the Raman spectra of pure constituents and several Lorentz peaks by a nonlinear least-square optimization algorithm. The content of the unknown alkane component C4+can be described as the area of CH deformation vibration peak common for most alkane molecules. Samples of the training set are used to establish the model between Raman characteristic peak area and corresponding concentration for each component relative to methane. Compared with the existing Raman analysis methods,the new method solves the issue of analyzing natural gas containing unknown alkane components and has good stability and accuracy. Experiments show that the maximum absolute errors of this algorithm for methane, ethane, propane, carbon dioxide, nitrogen, hydrogen, and carbon monoxide respectively reach 0.57%,0.37%,0.21%,0.07%,0.18%,0.04%,0.13%,and the correlation coefficient of gas chromatographic results also reaches 0. 997,0. 986,0. 991,0. 998,0. 993,1. 000,0. 995,0. 982,respectively.
引文
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2 Buric M,Mullen J,Chorpening B,Woodruff S. Proceedings of SPIE-The International Society for Optical Engineering,2014,9083:90830U
3 ZENG Wen-Ping,LUO Qin. Petroleum and Natural Gas Chemical,2015,44(3):104-108曾文平,罗勤.石油与天然气化工,2015,44(3):104-108
4 ZHU Hua-Dong,LUO Qin,ZHOU Li,TANG Meng,CHANG Hong-Gang. Natural Gas Industry,2013,33(11):110-114朱华东,罗勤,周理,唐蒙,常宏岗.天然气工业,2013,33(11):110-114
5 Sharma R,Poonacha S,Bekal A,Vartak S,Weling A,Tilak V,Mitra C. Opt. Engineer.,2016,55(10):104103
6 Zhao L,Chen W,Wan F,Shi J. Electrical Insulation and Dielectric Phenomena. IEEE,2013:1145-1148
7 KONG De-Jing,ZHAI Zhong-Sheng,WANG Xuan-Ze,HE Tao,XIONG Zhi,LIU Zhi-Qiang. Opto-Electronic Engineering,2016,43(4):20-26孔德靖,翟中生,王选择,何涛,熊芝,刘志强.光电工程,2016,43(4):20-26
8 LI Jin-Rong,DAI Lian-Kui,ZHOU Xiao-Li,ZHOU Yang. Chinese J. Anal. Chem.,2014,42(10):1518-1523李津蓉,戴连奎,武晓莉,周扬.分析化学,2014,42(10):1518-1523
9 CHEN Xin-Gang,YANG Ding-Kun,TAN Hao,MA Jun,TAN Yu-Miao. High Volatage Engineering,2017,43(7):2256-2262陈新岗,杨定坤,谭昊,马骏,谭毓苗.高压电技术,2017,43(7):2256-2262
10 Bayraktar S,Labitzke B,Bader J,Bornemann R,Bolivar P H,Kolb A. IEEE International Conference on Signal and Image Processing Applications. IEEE,2013:317-321
11 Buldakov M A,Korolkov V A,Matrosov I I,Petrov D V,Tikhomirov A A,Korolev B V. J. Opt. Technol.,2013,80(7):426-430
12 Petrov D V,Matrosov I I. Appl. Spectrosc.,2016,70(10):1770-1776
13 Kriesten E,Mayer D,Alsmeyer F,Minnich C B,Greiner L,Marquardt W. Chemometr. Intell. Lab. Sys.,2008,93(2):108-119
2 Buric M,Mullen J,Chorpening B,Woodruff S. Proceedings of SPIE-The International Society for Optical Engineering,2014,9083:90830U
3 ZENG Wen-Ping,LUO Qin. Petroleum and Natural Gas Chemical,2015,44(3):104-108曾文平,罗勤.石油与天然气化工,2015,44(3):104-108
4 ZHU Hua-Dong,LUO Qin,ZHOU Li,TANG Meng,CHANG Hong-Gang. Natural Gas Industry,2013,33(11):110-114朱华东,罗勤,周理,唐蒙,常宏岗.天然气工业,2013,33(11):110-114
5 Sharma R,Poonacha S,Bekal A,Vartak S,Weling A,Tilak V,Mitra C. Opt. Engineer.,2016,55(10):104103
6 Zhao L,Chen W,Wan F,Shi J. Electrical Insulation and Dielectric Phenomena. IEEE,2013:1145-1148
7 KONG De-Jing,ZHAI Zhong-Sheng,WANG Xuan-Ze,HE Tao,XIONG Zhi,LIU Zhi-Qiang. Opto-Electronic Engineering,2016,43(4):20-26孔德靖,翟中生,王选择,何涛,熊芝,刘志强.光电工程,2016,43(4):20-26
8 LI Jin-Rong,DAI Lian-Kui,ZHOU Xiao-Li,ZHOU Yang. Chinese J. Anal. Chem.,2014,42(10):1518-1523李津蓉,戴连奎,武晓莉,周扬.分析化学,2014,42(10):1518-1523
9 CHEN Xin-Gang,YANG Ding-Kun,TAN Hao,MA Jun,TAN Yu-Miao. High Volatage Engineering,2017,43(7):2256-2262陈新岗,杨定坤,谭昊,马骏,谭毓苗.高压电技术,2017,43(7):2256-2262
10 Bayraktar S,Labitzke B,Bader J,Bornemann R,Bolivar P H,Kolb A. IEEE International Conference on Signal and Image Processing Applications. IEEE,2013:317-321
11 Buldakov M A,Korolkov V A,Matrosov I I,Petrov D V,Tikhomirov A A,Korolev B V. J. Opt. Technol.,2013,80(7):426-430
12 Petrov D V,Matrosov I I. Appl. Spectrosc.,2016,70(10):1770-1776
13 Kriesten E,Mayer D,Alsmeyer F,Minnich C B,Greiner L,Marquardt W. Chemometr. Intell. Lab. Sys.,2008,93(2):108-119