Citation: | WANG Guan-cheng, ZHAO Bai-xuan, ZHENG Kai-feng, CHEN Yu-peng, ZHAO Ying-ze, QIN Yu-xin, WANG Wei-biao, LIU Guo-hao, SHENG Kai-yang, LV Jin-guang, LIANG Jing-qiu. Research on high-precision gas concentration inversion based on adaptive infrared multi-band joint spectral analysis[J]. Chinese Optics. doi: 10.37188/CO.2024-0071 |
Fourier transform spectroscopy (FTS) is an effective method for gas composition analysis and accurate measurement of concentration. However, in the process of analysis, the saturated absorption and weak absorption of the measured gas make the transmittance of some bands deviate from the stable range, which leads to the decrease of spectral signal-to-noise ratio and the nonlinear response of the instrument, and reduces the accuracy of concentration inversion.
In this paper, an adaptive multi-band joint concentration inversion algorithm is proposed, which combines the transmittance stable range and the spectral width threshold to adaptively select the effective band of the measured gas. The nonlinear least squares fitting method is used to invert the concentration of each effective band and the residual analysis is carried out to obtain the concentration inversion results and their weights of each effective band. The accurate quantitative analysis of the measured gas is realized by weighted average.
: The algorithm verification experiment is designed and carried out; the results show that the stability coefficient of the adaptive multi-band joint concentration inversion algorithm is 0.9976. Compared with the traditional single-band and multi-band concentration inversion algorithms, the root mean square error of the inversion results is reduced by 64.44% and 41.52%, the mean relative error is reduced by 65.97% and 46.72%, and the mean absolute error is reduced by 66.32% and 47.74% respectively,
the inversion accuracy and stability are significantly improved.
[1] |
CUISSET A, VENABLES D S, GAO X M, et al. Applications of spectroscopy in environmental monitoring of gases and aerosols[J]. Journal of Spectroscopy, 2016, 2016: 2575782.
|
[2] |
YANG CH, ZHOU ZH Y, LI Y, et al. Measuring the tuning curve of spontaneous parameter downconversion using a comet-tail-like pattern[J]. Optics Letters, 2022, 47(4): 898-901. doi: 10.1364/OL.447674
|
[3] |
TALGHADER J J, GAWARIKAR A S, SHEA R P. Spectral selectivity in infrared thermal detection[J]. Light: Science & Applications, 2012, 1(8): e24.
|
[4] |
ZHAO B X, LIANG J Q, LV J G, et al. Reducing the influence of systematic errors in interference core of stepped micro-mirror imaging fourier transform spectrometer: a novel calibration method[J]. Remote Sensing, 2023, 15(4): 985. doi: 10.3390/rs15040985
|
[5] |
张璐, 李博, 李寒霜, 等. 超光谱分辨率紫外双通道共光路成像光谱仪设计[J]. 中国光学(中英文),2022,15(5):1029-1037. doi: 10.37188/CO.2022-0125
ZHANG L, LI B, LI H SH, et al. Hyperspectral resolution ultraviolet dual channel common optical path imaging spectrometer[J]. Chinese Optics, 2022, 15(5): 1029-1037. (in Chinese). doi: 10.37188/CO.2022-0125
|
[6] |
LI A, YAO CH H, XIA J F, et al. Advances in cost-effective integrated spectrometers[J]. Light: Science & Applications, 2022, 11(1): 174.
|
[7] |
ARRIGONE G M, HILTON M. Theory and practice in using Fourier transform infrared spectroscopy to detect hydrocarbons in emissions from gas turbine engines[J]. Fuel, 2005, 84(9): 1052-1058. doi: 10.1016/j.fuel.2005.01.018
|
[8] |
刘成员, 于江玉, 李奉翠, 等. 拉曼光谱测试技术在可充电铝离子电池储能机理的研究进展[J]. 应用化学,2023,40(10):1347-1358.
LIU CH Y, YU J Y, LI F C, et al. Research progress of Raman spectroscopy technique in energy storage mechanism of rechargeable aluminum-ion batteries[J]. Chinese Journal of Applied Chemistry, 2023, 40(10): 1347-1358. (in Chinese).
|
[9] |
仝大伟, 孔明, 向育斌. 含甲氧基四苯乙烯咪唑化合物的合成、光物理性质、理论计算及细胞成像[J]. 应用化学,2023,40(9):1322-1333.
TONG D W, KONG M, XIANG Y B. Synthesis, photophysical properties, theoretical calculation and cell imaging of a tetraphenylethene imidazole compound with methoxy group[J]. Chinese Journal of Applied Chemistry, 2023, 40(9): 1322-1333. (in Chinese).
|
[10] |
舒开强, 陈友元, 彭郑英, 等. 铀矿中多目标元素的激光诱导击穿光谱定量分析方法研究[J]. 分析化学,2023,51(7):1195-1203.
SHU K Q, CHEN Y Y, PENG ZH Y, et al. Laser-induced breakdown spectroscopy for quantitative analysis of multi-target elements in uranium ore[J]. Chinese Journal of Analytical Chemistry, 2023, 51(7): 1195-1203. (in Chinese).
|
[11] |
陈玥瑶, 夏静静, 韦芸, 等. 近红外光谱法无损检测平谷产大桃品质方法研究[J]. 分析化学,2023,51(3):454-462.
CHEN Y Y, XIA J J, WEI Y, et al. Research on nondestructive quality test of Pinggu peach by near-infrared spectroscopy[J]. Chinese Journal of Analytical Chemistry, 2023, 51(3): 454-462. (in Chinese).
|
[12] |
LI H L, DI S, LV W J, et al. Research on the measurement of CO2 concentration based on multi-band fusion model[J]. Applied Physics B, 2021, 127(1): 5. doi: 10.1007/s00340-020-07564-8
|
[13] |
CIĘSZCZYK S. A multi-band integrated virtual calibration-inversion method for open path ftir spectrometry[J]. Metrology and Measurement Systems, 2013, 20(2): 287-298. doi: 10.2478/mms-2013-0025
|
[14] |
吴时超. 基于中波红外光谱信息的大气CO2反演方法[D]. 合肥: 中国科学技术大学, 2021.
WU SH CH. Atmospheric CO2 inversion method based on mid-wave infrared spectral information[D]. Hefei: University of Science and Technology of China, 2021. (in Chinese).
|
[15] |
WANG W ZH, WANG Y M, SONG W J, et al. Multiband infrared inversion for low-concentration methane monitoring in a confined dust-polluted atmosphere[J]. Applied Optics, 2017, 56(9): 2548-2555. doi: 10.1364/AO.56.002548
|
[16] |
吴靖, 张朋朋, 黄峰, 等. NO2双通道光谱成像定量监测技术研究[J]. 仪器仪表学报,2022,43(4):155-162.
WU J, ZHANG P P, HUANG F, et al. Research on quantitative monitoring technology of NO2 dual-channel spectral imaging[J]. Chinese Journal of Scientific Instrument, 2022, 43(4): 155-162. (in Chinese).
|
[17] |
周佳巧, 崔文楠, 张涛, 等. 基于光谱测量数据的自适应波段选择技术[J]. 激光与光电子学进展,2019,56(23):232501.
ZHOU J Q, CUI W N, ZHANG T, et al. Adaptive band selection technique based on spectral measurement data[J]. Laser & Optoelectronics Progress, 2019, 56(23): 232501. (in Chinese).
|
[18] |
HAALAND D M, HAN L, NIEMCZYK T M. Use of CLS to understand PLS IR calibration for trace detection of organic molecules in water[J]. Applied Spectroscopy, 1999, 53(4): 390-395. doi: 10.1366/0003702991946848
|
[19] |
CHUKWU R, MUGISA J, BROGIOLI D, et al. Statistical analysis of the measurement noise in dynamic impedance spectra[J]. Chemelectrochem, 2022, 9(14): e202200109. doi: 10.1002/celc.202200109
|
[20] |
刘海涛, 魏汝祥, 蒋国萍. 基于加权偏最小二乘回归的软件成本估算方法[J]. 计算机工程,2012,38(21):36-39. doi: 10.3969/j.issn.1000-3428.2012.21.010
LIU H T, WEI R X, JIANG G P. Software cost estimation method based on weighted partial least squares regression[J]. Computer Engineering, 2012, 38(21): 36-39. (in Chinese). doi: 10.3969/j.issn.1000-3428.2012.21.010
|
[21] |
齐亚欣, 陈嵩. 一种基于多元回归的射线数字图像影响因子的权重分配方法[J]. 无损检测,2018,40(8):6-9,14. doi: 10.11973/wsjc201808002
QI Y X, CHEN S. A weight assignment method for influencing factors of radiographic digital images based on multiple regression[J]. Nondestructive Testing, 2018, 40(8): 6-9,14. (in Chinese). doi: 10.11973/wsjc201808002
|
[22] |
CONDE O M, DE LA CRUZ J, RODRIGUEZ-COBO L, et al. Optimized image calibration for spectroscopic systems[C]. Proceedings of 2011 IEEE SENSORS, IEEE, 2011.
|
[23] |
DRYJAŃSKI P. Error analysis of infrared transmission measurements: determination of baseline, choice of peak maximum and range truncation in band profile and integrated intensity determination[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 1998, 54(2): 265-276. doi: 10.1016/S1386-1425(97)00215-1
|
[24] |
LIU H, ZHU J, YIN H, et al. Extreme learning machine and genetic algorithm in quantitative analysis of sulfur hexafluoride by infrared spectroscopy: erratum[J]. Applied Optics, 2023, 62(23): 6169-6170. doi: 10.1364/AO.499761
|
[25] |
张豹, 高潮, 郭永彩, 等. 基于DOAS及统计量的低浓度SO2测量方法(英文)[J]. 光子学报,2018,47(2):0230001.
ZHANG B, GAO CH, GUO Y C, et al. Measurement method for low-concentration SO2 based on statistics and DOAS[J]. Acta Photonica Sinica, 2018, 47(2): 0230001. (查阅网上资料, 本条文献为英文文献, 请确认) .
|
[26] |
程巳阳, 张天舒, 高闽光, 等. FTIR光谱高温气体浓度反演方法及残差结构分析[J]. 光谱学与光谱分析,2011,31(1):82-85. doi: 10.3964/j.issn.1000-0593(2011)01-0082-04
CHENG S Y, ZHANG T SH, GAO M G, et al. Concentration inversion of high temperature air from FTIR spectra and analyzing residual error structure[J]. Spectroscopy and Spectral Analysis, 2011, 31(1): 82-85. (in Chinese). doi: 10.3964/j.issn.1000-0593(2011)01-0082-04
|
[27] |
NIE W, XU ZH Y, RAO G F, et al. Methods of tunable diode laser absorption saturation spectroscopy to gas sensing under optically thick conditions[J]. Microwave and Optical Technology Letters, 2021, 63(8): 2063-2067. doi: 10.1002/mop.32840
|
[28] |
CAI Y F, XU ZH, JI K F. Measurement and correction of instrumental profiles for the spectral data of the new vacuum solar telescope[J]. Solar Physics, 2020, 295(2): 31. doi: 10.1007/s11207-020-1598-0
|
[29] |
WANG F, MA S X, YAN G W. A PLS-based random forest for NOx emission measurement of power plant[J]. Chemometrics and Intelligent Laboratory Systems, 2023, 240: 104926. doi: 10.1016/j.chemolab.2023.104926
|
[30] |
PEI X K, GIDON D, YANG Y J, et al. Reducing energy cost of NO x production in air plasmas[J]. Chemical Engineering Journal, 2019, 362: 217-228. doi: 10.1016/j.cej.2019.01.011
|