光谱学与光谱分析 |
|
|
|
|
|
On-Line and In-Situ Spectral Analysis of Multicomponent Gas Mixture with Same Molecular Group |
TANG Xiao-jun, LI Yu-jun, ZHU Ling-jian, DING Hui, LIU Jun-hua |
State Key Laboratory of Electrical Insulation & Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China |
|
|
Abstract Aimed at the problem that Fourier transform infrared (FTIR) spectral analysis can’t be used solely to analyze complex gas mxiture, in which there are many gas compositions, some compositions have same molecular group, and the concentrations of some compositions range greatly, in the present paper, a new spectral analysis method is proposed. For this method, the effects of gas temperature and gas pressure on the analysis result are taken into account, and feature variable extraction, recognition and correction of spectral disorder, robust modeling and multi-layer modeling with neural network (NN) are used to build gas mixture analysis models. At the end of this paper, on-line analysis of five alkane gases is taken as example to test the performance of the analysis method. CH4, C2H6, C3H8, iso-C4H10 and n-C4H10 are taken as object gases while iso-C5H12 and n-C5H12 are looked as disturbing gases. The comparison results that analysis result curves of FTIR overlap that of gas chromatograph indicate that FTIR can be solely used in on-line and in-situ analysis of multicomponent gas mixture with same molecular group if the analysis method presented in this paper is used.
|
Received: 2011-01-18
Accepted: 2011-04-22
|
|
Corresponding Authors:
TANG Xiao-jun
E-mail: xiaojun_tang@mail.xjtu.edu.cn
|
|
[1] Griffiths P R, de Haseth J A. Fourier Transform Infrared Spectrometry. New Jersey: John Wiley & Sons, Inc, 2007. [2] Kim B, Kwon M J. Applied Spectroscopy, 2008, 62(1): 73. [3] Usseglio S, Thorshaug K, Karlsson A, et al. Applied Spectroscopy, 2010, 64(2): 141. [4] Sepman A V, Blackmen R D, Schepers R, et al. Applied Spectroscopy, 2009, 63(11): 1211. [5] He Yihua, Tang Li, Wu Xi, et al. Applied Spectroscopy Reviews, 2007, (42): 119. [6] Liland K H, Almoy T, Mevik B H. Applied Spectroscopy, 2010, 64(9): 1007. [7] Stout F, Kalivas J H, Heberger K. Applied Spectroscopy, 2007, 61(1): 85. [8] Yang H, Griffiths P R, Tate J D. Analytica Chimica Acta, 2003, 489: 125. [9] Schmitt M, Biemann L, Meerts W L, et al. Journal of Molecular Spectroscopy, 2009, 257: 74. [10] LIU Jun-hua, TANG Xiao-jun(刘君华, 汤晓君). Invention Patent, 03134431. 3, 2005. 6. 1. [11] Majdi A, Beiki M, Pirayehgar A, et al. Journal of Petroleum Science and Engineering, 2010, 75: 91. |
[1] |
LI Xin-ting, ZHANG Feng, FENG Jie*. Convolutional Neural Network Combined With Improved Spectral
Processing Method for Potato Disease Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 215-224. |
[2] |
LAN Yan1,WANG Wu1,XU Wen2,CHAI Qin-qin1*,LI Yu-rong1,ZHANG Xun2. Discrimination of Planting and Tissue-Cultured Anoectochilus Roxburghii Based on SMOTE and Inception-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 158-163. |
[3] |
LI Hu1, ZHONG Yun1, 2, FENG Ya-ting1, LIN Zhen1, ZHU Shi-jiang1, 2*. Multi-Vegetation Index Soil Moisture Inversion Model Based on UAV
Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 207-214. |
[4] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
[5] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
[6] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
[7] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
[8] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
[9] |
SUN Cheng-yu1, JIAO Long1*, YAN Na-ying1, YAN Chun-hua1, QU Le2, ZHANG Sheng-rui3, MA Ling1. Identification of Salvia Miltiorrhiza From Different Origins by Laser
Induced Breakdown Spectroscopy Combined with Artificial Neural
Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3098-3104. |
[10] |
LIU Shu1, JIN Yue1, 2, SU Piao1, 2, MIN Hong1, AN Ya-rui2, WU Xiao-hong1*. Determination of Calcium, Magnesium, Aluminium and Silicon Content in Iron Ore Using Laser-Induced Breakdown Spectroscopy Assisted by Variable Importance-Back Propagation Artificial Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3132-3142. |
[11] |
CAI Jian-rong1, 2, HUANG Chu-jun1, MA Li-xin1, ZHAI Li-xiang1, GUO Zhi-ming1, 3*. Hand-Held Visible/Near Infrared Nondestructive Detection System for Soluble Solid Content in Mandarin by 1D-CNN Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2792-2798. |
[12] |
PU Shan-shan, ZHENG En-rang*, CHEN Bei. Research on A Classification Algorithm of Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2446-2451. |
[13] |
ZHU Yan-ping1, CUI Chuan-jin1*, CHENG Peng-fei1, 2, PAN Jin-yan1, SU Hao1, 2, ZHANG Yi1. Measurement of Oil Pollutants by Three-Dimensional Fluorescence
Spectroscopy Combined With BP Neural Network and SWATLD[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2467-2475. |
[14] |
TANG Ting, PAN Xin*, LUO Xiao-ling, GAO Xiao-jing. Fusion of ConvLSTM and Multi-Attention Mechanism Network for
Hyperspectral Image Classification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2608-2616. |
[15] |
LIU Zhao1, 2, LI Hua-peng1, CHEN Hui1, 2, ZHANG Shu-qing1*. Maize Yield Forecasting and Associated Optimum Lead Time Research Based on Temporal Remote Sensing Data and Different Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2627-2637. |
|
|
|
|