混合气体测量中重叠吸收谱线交叉干扰的分离解析方法

王前进; 孙鹏帅; 张志荣; 张乐文; 杨曦; 吴边; 庞涛; 夏滑; 李启勇

doi:10.7498/aps.70.20210286

摘要

在基于可调谐二极管激光吸收光谱技术(tunable diode laser absorption spectroscopy, TDLAS)进行多种组分混合气体测量时, 经常会遇到吸收谱线之间存在相互干扰的现象, 这也是使用该技术测量过程中的主要“瓶颈”. 比如在前期的应用中: 微量一氧化碳(CO)和甲烷气体(CH₄)在同时检测时两者的吸收谱线存在严重的重叠干扰现象, 特别是在高浓度CH₄存在的环境下, 微量CO气体吸收信号会被干扰甚至湮没, 无法实现有效解调, 这是通过谱线选取所不能解决的问题. 因此, 针对此问题本文提出了基于支持向量回归模型, 以CO和CH₄吸收谱线的严重重叠干扰问题为例, 通过选择线性核函数建立CO支持向量回归模型和CH₄支持向量回归模型, 可对CO和CH₄的混合气体吸收谱线进行解调, 最终获得两种气体浓度的准确测量结果. 通过实验分别实现了四种不同浓度CH₄环境下微量CO气体的检测, 得到的CO和CH₄浓度(气体的体积分数)测量的绝对误差分别小于2 × 10^–6和0.2 × 10^–2; 通过不同浓度的固定配比实验分析, CO和CH₄气体的测量值与实际值之间的相关系数分别达到了0.998和0.9995, 且CO和CH₄气体测量结果的绝对误差分别不超过2 × 10^–6和0.1 × 10^–2, 完全满足了混合气体的精确测量, 为实现多场合混合气体目标的实时监测提出了解决方案.

关键词:

Abstract

The interference between overlapping gas absorption lines often occurs in the measurement of multi-component gas mixture with using tunable diode laser absorption spectroscopy (TDLAS). This is also the main problem of the technology in some applications. For instance, in the early application of multi-component gas mixture measurement in coal mines, we found that the absorption lines of carbon monoxide (CO) and methane (CH₄) seriously overlapped. The absorption signal of trace CO gas was annihilated and could not be effectively demodulated, especially in the presence of high concentration of CH₄. This problem could not be solved just by accurately selecting the spectral lines due to the band absorption of CH₄. Therefore, in this paper, we introduce the support vector regression (SVR) model to deal with the interference between CO and CH₄ absorption lines. The spectral signals of 14 groups of mixed gases with different concentrations of CO and CH₄ are used as the training sets, and the five-fold cross-validation is adopted to prevent the model from overfitting. After 15 iterations in 30 seconds, the optimal regression model of CO and CH₄ can be obtained respectively. Furthermore, it is worth noting that based on the experimental data, the linear kernel function is selected to construct the two gas SVR models, and the parameters of the SVR models are optimized by the sequential minimal optimization(SMO) algorithm. With the assistance of the SVR models, the absorption spectra of the two gases can be demodulated effectively, and finally the accurate measurement results are obtained. The measurement results show that the absolute error of trace CO and CH₄ concentration(volume fraction of gas) are less than 2 × 10^–6 and 0.2 × 10^–2 respectively. Meanwhile, the correlation coefficient between the measured values and the actual values of CO and CH₄ are 0.998 and 0.9995, respectively. In addition, the dynamic stability for each of the two regression models is fully verified by the experiment of the inflation process. Consequently, this method can eliminate the interference between the overlapping spectra, and can fully meet the requirements for accurately measuring the gas mixture. We hope that the SVR model can provide an effective solution for the real-time monitoring of multi-component gas mixture, and thus greatly improving the adaptability of TDLAS technology in the future.

Keywords:

tunable diode laser absorption spectroscopy (TDLAS) /
gas mixture /
overlapping spectral lines /
support vector regression

作者及机构信息

1.
中国科学技术大学环境科学与光电技术学院, 合肥　230026

2.
中国科学院合肥物质科学研究院安徽光学精密机械研究所, 光子器件与材料安徽省重点实验室, 合肥　230031

3.
中国科学院合肥物质科学研究院安徽光学精密机械研究所, 中国科学院环境光学与技术重点实验室, 合肥　230031

4.
国防科技大学, 先进激光技术安徽省实验室, 合肥　230037

5.
中国科学技术大学, 合肥　230022

6.
安徽省生态环境监测中心, 合肥　230071

通信作者: 张志荣, zhangzr@aiofm.ac.cn

基金项目: 国家自然科学基金(批准号: 11874364, 41877311, 42005107)、国家重点研发计划(批准号: 2017YFC0805004)、安徽省重点研究与开发计划项目(批准号: 201904c03020005)和中国科学院合肥研究院“火花”基金项目(批准号: YZJJ2020QN8)资助的课题

Authors and contacts

1.
School of Environment Science and Optoelectronic Technology, University of Science and Technology of China, Hefei 230026, China

2.
Anhui Provincial Key Laboratory of Photonic Devices and Materials, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

3.
Key Laboratory of Environmental Optics & Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China

4.
Advanced Laser Technology Laboratory of Anhui Province, National University of Defense Technology, Hefei 230037, China

5.
University of Science and Technology of China, Hefei 230022, China

6.
Monitoring Center of Ecology and Environment of Anhui Province, Hefei 230071, China

Corresponding author: Zhang Zhi-Rong, zhangzr@aiofm.ac.cn

Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 11874364, 41877311, 42005107), the National Key Research and Development Program of China (Grant No. 2017YFC0805004), the Key Research and Development Projects of Anhui Province, China (Grant No. 201904c03020005), and the "Spark" Fund Project of Hefei Institutes of Physics Science, Chinese Academy Sciences, China (Grant No. YZJJ2020QN8)

文章全文 : translate this paragraph

参考文献

[1]	Zhang Z R, Pang T, Yang Y, Xia H, Cui X J, Sun P S, Wu B, Wang Y, Sigrist M W, Dong F Z 2016 Opt. Express 24 A943 Google Scholar
[2]	Wang F P, Chang J, Wang Q, Wei W, Qin Z G 2017 Sens. Actuators A 259 152 Google Scholar
[3]	Avetisov V, Bjoroey O, Wang J, Geiser P, Paulsen K G 2019 Sensors 19 5313 Google Scholar
[4]	Nwaboh J A, Werhahn O, Ortwein P, Schiel D, Ebert V 2013 Meas. Sci. Technol. 24 015202 Google Scholar
[5]	Vallon R, Soutade J, Verant J L, Meyers J, Paris S, Mohamed A 2010 Sensors 10 6081 Google Scholar
[6]	夏滑, 吴边, 张志荣, 庞涛, 董凤忠, 王煜 2013 物理学报 62 214208 Google Scholar Xia H, Wu B, Zhang Z R, Pang T, Dong F Z, Wang Y 2013 Acta Phys. Sin. 62 214208 Google Scholar
[7]	Zhang L W, Zhang Z R, Sun P S, Pang T, Xia H, Cui X J, Guo Q, Sigrist M W, Shu C M, Shu Z F 2020 Spectrochim. Acta, Part A 239 118495 Google Scholar
[8]	He Q X, Dang P P, Liu Z W, Zheng C T, Wang Y D 2017 Opt. Quantum Electron. 49 115 Google Scholar
[9]	Kluczynski P, Gustafsson J, Lindberg A M, Axner O 2001 Spectrochim. Acta, Part B 56 1277 Google Scholar
[10]	Wang F, Wu Q, Huang Q X, Zhang H D, Yan J H, Cen K F 2015 Opt. Commun. 346 53 Google Scholar
[11]	Lin X, Yu X L, Li F, Zhang S H, Xin J G, Chang X Y 2013 Appl. Phys. B: Lasers Opt. 110 401 Google Scholar
[12]	Köhring M, Huang S, Jahjah M, Jiang W, Ren W, Willer U, Caneba C, Yang L, Nagrath D, Schade W, Tittel F K 2014 Appl. Phys. B 117 445 Google Scholar
[13]	Zhang T, Kang J, Meng D, Wang H, Mu Z, Zhou M, Zhang X, Chen C 2018 Sensors 18 4295 Google Scholar
[14]	张志荣, 吴边, 夏滑, 庞涛, 王高旋, 孙鹏帅, 董凤忠, 王煜 2013 物理学报 62 234204 Google Scholar Zhang Z R, Wu B, Xia H, Pang T, Wang G X, Sun P S, Dong F Z, Wang Y 2013 Acta Phys. Sin. 62 234204 Google Scholar
[15]	Gabrysch M, Corsi C, Pavone F S, Inguscio M 1997 Appl. Phys. B 65 75 Google Scholar
[16]	Cai T D, Gao G Z, Wang M R 2016 Opt. Express 24 859 Google Scholar
[17]	Malegori C, Marques E J N, Freitas S T d, Pimentel M F, Pasquini C, Casiraghi E 2017 Talanta 165 112 Google Scholar
[18]	张志荣, 夏滑, 董凤忠, 庞涛, 吴边 2013 光学精密工程 21 2771 Google Scholar Zhang Z R, Xia H, Dong F Z, Pang T, Wu B 2013 Opt. Precis. Eng. 21 2771 Google Scholar
[19]	Shao L G, Fang B, Zheng F, Qiu X B, He Q S, Wei J L, Li C L, Zhao W X 2019 Spectrochim. Acta, Part A 222 117118 Google Scholar
[20]	Qu J, Chen H Y, Liu W Z, Zhang B, Li Z B 2015 Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering Zhengzhou, PRC, April 11−13, 2015 p2111
[21]	Laref R, Losson E, Sava A, Adjallah K, Siadat M 2018 2018 Ieee International Conference on Industrial Technology (Icit) Lyon, France, February 19−22, 2018 p1335
[22]	Reid J, Labrie D 1981 Appl. Phys. B 26 203
[23]	Smola A J, Scholkopf B 2004 Stat. Comput. 14 199 Google Scholar
[24]	Gordon I E, Rothman L S, Hill C, et al. 2017 J. Quant. Spectrosc. Radiat. Transfer 203 3 Google Scholar

施引文献

图 1 DFB激光器电流-波长调谐性能曲线

Fig. 1. Current-wavelength tuning curve of DFB laser.

下载: 全尺寸图片幻灯片

图 2 实验系统原理图

Fig. 2. Schematic diagram of the experimental system.

下载: 全尺寸图片幻灯片

图 3 CO (20 × 10^–6, 400 × 10^–6)和CH₄(1 × 10^–2)的模拟吸收光谱图

Fig. 3. Simulated absorption spectra of CO (20 × 10^–6, 400 × 10^–6) and CH₄ (1 × 10^–2).

下载: 全尺寸图片幻灯片

图 4 三组气体(Group 1、Group 4、Group 10)的2f/1f信号

Fig. 4. 2f/1f signals of three groups of gases (Group 1, Group 4, Group 10).

下载: 全尺寸图片幻灯片

图 5 CO和CH₄浓度设置值和测试值对比　(a) CO浓度值; (b) CH₄浓度值

Fig. 5. Comparisons between set and test values: (a) CO concentration; (b) CH₄ concentration.

下载: 全尺寸图片幻灯片

图 6 设置值和测量值之间相关性及测量误差　(a) CO相关性; (b) CH₄相关性; (c) CO测量误差; (d) CH₄测量误差

Fig. 6. Correlation and test errors between set and average values: (a) CO correlation; (b) CH₄ correlation; (c) CO errors; (d) CH₄ errors.

下载: 全尺寸图片幻灯片

图 7 不同浓度CH₄对CO测量结果的干扰

Fig. 7. Interference on CO measurement results by different concentrations of CH₄.

下载: 全尺寸图片幻灯片

图 8 第一组充气过程中CO和CH₄浓度变化

Fig. 8. Concentration measured of CO and CH₄ during the first set of inflation.

下载: 全尺寸图片幻灯片

图 9 第二组充气过程中CO和CH₄浓度变化

Fig. 9. Concentration measured of CO and CH₄ during the second set of inflation.

下载: 全尺寸图片幻灯片

表 1 训练数据集

Table 1. Training data set.

Group	Standard gas category and concentration		Ratio	Gas category and concentration in multi-pass cell
Group	CO/10^–6	CH₄/10^–2	Ratio	CO/10^–6	CH₄/10^–2
1	19.3	0	—	19.3	0
2	54.0	0	—	54.0	0
3	102.0	0	—	102.0	0
4	0	0.50	—	0	0.50
5	0	1.04	—	0	1.04
6	0	2.02	—	0	2.02
7	0	5.02	—	0	5.02
8	54.0	1.04	1∶1	27.0	0.52
9	102.0	1.04	1∶1	51.0	0.52
10	19.3	1.04	1∶1	9.6	0.52
11	19.3	0.50	1∶1	9.6	0.25
12	19.3	5.02	1∶1	9.6	2.51
13	19.3	2.02	1∶1	9.6	1.01
14	19.3	8.50	1∶1	9.6	4.25

下载: 导出CSV

表 2 SVR模型主要参数

Table 2. Optimal parameters of SVR model.

	CO-SVRmodel	CH₄-SVRmodel
BoxConstraint(C )	0.3443	0.0180
KernelScale	0.0617	0.9205
ε	0.1710	65.1810
Total function evaluations	15	15
Total elapsed time in seconds	26.2545	12.5730

下载: 导出CSV

[1]	Zhang Z R, Pang T, Yang Y, Xia H, Cui X J, Sun P S, Wu B, Wang Y, Sigrist M W, Dong F Z 2016 Opt. Express 24 A943 Google Scholar
[2]	Wang F P, Chang J, Wang Q, Wei W, Qin Z G 2017 Sens. Actuators A 259 152 Google Scholar
[3]	Avetisov V, Bjoroey O, Wang J, Geiser P, Paulsen K G 2019 Sensors 19 5313 Google Scholar
[4]	Nwaboh J A, Werhahn O, Ortwein P, Schiel D, Ebert V 2013 Meas. Sci. Technol. 24 015202 Google Scholar
[5]	Vallon R, Soutade J, Verant J L, Meyers J, Paris S, Mohamed A 2010 Sensors 10 6081 Google Scholar
[6]	夏滑, 吴边, 张志荣, 庞涛, 董凤忠, 王煜 2013 物理学报 62 214208 Google Scholar Xia H, Wu B, Zhang Z R, Pang T, Dong F Z, Wang Y 2013 Acta Phys. Sin. 62 214208 Google Scholar
[7]	Zhang L W, Zhang Z R, Sun P S, Pang T, Xia H, Cui X J, Guo Q, Sigrist M W, Shu C M, Shu Z F 2020 Spectrochim. Acta, Part A 239 118495 Google Scholar
[8]	He Q X, Dang P P, Liu Z W, Zheng C T, Wang Y D 2017 Opt. Quantum Electron. 49 115 Google Scholar
[9]	Kluczynski P, Gustafsson J, Lindberg A M, Axner O 2001 Spectrochim. Acta, Part B 56 1277 Google Scholar
[10]	Wang F, Wu Q, Huang Q X, Zhang H D, Yan J H, Cen K F 2015 Opt. Commun. 346 53 Google Scholar
[11]	Lin X, Yu X L, Li F, Zhang S H, Xin J G, Chang X Y 2013 Appl. Phys. B: Lasers Opt. 110 401 Google Scholar
[12]	Köhring M, Huang S, Jahjah M, Jiang W, Ren W, Willer U, Caneba C, Yang L, Nagrath D, Schade W, Tittel F K 2014 Appl. Phys. B 117 445 Google Scholar
[13]	Zhang T, Kang J, Meng D, Wang H, Mu Z, Zhou M, Zhang X, Chen C 2018 Sensors 18 4295 Google Scholar
[14]	张志荣, 吴边, 夏滑, 庞涛, 王高旋, 孙鹏帅, 董凤忠, 王煜 2013 物理学报 62 234204 Google Scholar Zhang Z R, Wu B, Xia H, Pang T, Wang G X, Sun P S, Dong F Z, Wang Y 2013 Acta Phys. Sin. 62 234204 Google Scholar
[15]	Gabrysch M, Corsi C, Pavone F S, Inguscio M 1997 Appl. Phys. B 65 75 Google Scholar
[16]	Cai T D, Gao G Z, Wang M R 2016 Opt. Express 24 859 Google Scholar
[17]	Malegori C, Marques E J N, Freitas S T d, Pimentel M F, Pasquini C, Casiraghi E 2017 Talanta 165 112 Google Scholar
[18]	张志荣, 夏滑, 董凤忠, 庞涛, 吴边 2013 光学精密工程 21 2771 Google Scholar Zhang Z R, Xia H, Dong F Z, Pang T, Wu B 2013 Opt. Precis. Eng. 21 2771 Google Scholar
[19]	Shao L G, Fang B, Zheng F, Qiu X B, He Q S, Wei J L, Li C L, Zhao W X 2019 Spectrochim. Acta, Part A 222 117118 Google Scholar
[20]	Qu J, Chen H Y, Liu W Z, Zhang B, Li Z B 2015 Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering Zhengzhou, PRC, April 11−13, 2015 p2111
[21]	Laref R, Losson E, Sava A, Adjallah K, Siadat M 2018 2018 Ieee International Conference on Industrial Technology (Icit) Lyon, France, February 19−22, 2018 p1335
[22]	Reid J, Labrie D 1981 Appl. Phys. B 26 203
[23]	Smola A J, Scholkopf B 2004 Stat. Comput. 14 199 Google Scholar
[24]	Gordon I E, Rothman L S, Hill C, et al. 2017 J. Quant. Spectrosc. Radiat. Transfer 203 3 Google Scholar

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[20]	阚瑞峰, 刘文清, 张玉钧, 刘建国, 董凤忠, 高山虎, 王敏, 陈军. 可调谐二极管激光吸收光谱法测量环境空气中的甲烷含量. 物理学报, 2005, 54(4): 1927-1930. doi: 10.7498/aps.54.1927

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