Volume 43 Issue 6
Nov.  2022
Turn off MathJax
Article Contents
DENG Qin. High-precision detection technology of NO concentration based on UV differential-adaptive interference cancellation[J]. Journal of Applied Optics, 2022, 43(6): 1054-1060. doi: 10.5768/JAO202243.0604003
Citation: DENG Qin. High-precision detection technology of NO concentration based on UV differential-adaptive interference cancellation[J]. Journal of Applied Optics, 2022, 43(6): 1054-1060. doi: 10.5768/JAO202243.0604003

High-precision detection technology of NO concentration based on UV differential-adaptive interference cancellation

doi: 10.5768/JAO202243.0604003
  • Received Date: 2022-06-13
  • Rev Recd Date: 2022-08-03
  • Available Online: 2022-08-05
  • Publish Date: 2022-11-14
  • In order to realize high-precision monitoring of vehicle emission, a high-precision and wide-range NO measurement method was proposed. Aiming at the problem that the absorption peaks of SO2 and NO in emission overlapping in the UV band, and it was impossible to directly perform single-component gas inversion, the differential optical density (DOD) of mixed gas in the NO sensitive band (200 nm~230 nm) was first calculated by the ultraviolet differential optical absorption spectroscopy (UV-DOAS) method. Then, the adaptive interference cancellation technology was introduced to achieve rapid separation of mixed gas DOD. Finally, the least square method was used to perform the concentration inversion of separated NO. This method could achieve rapid inversion of NO concentration (volume fraction of gas) in the range of 100×10−6 to 3 000×10−6. After testing, the absolute value of the relative error of inversion is less than 10% in the concentration range of 100×10−6 to 200×10−6, and less than 5% in the concentration range of 300×10−6 to 3 000×10−6. This method has the characteristics of large measurement range and fast speed, and can meet the measurement requirements of NO concentration in the range of 3 000×10−6 in vehicle emission.
  • loading
  • [1]
    中华人民共和国公安部交通管理局. 全国机动车保有量及驾驶人数据统计(截止2021)[EB/OL]. http://www.gov.cn/xinwen/2022-01/11/content_5667669.htm, 2022.

    Ministry of Public Security, PRC Traffic Management Bureau. National motor vehicle ownership and driver data statistics[EB/OL]. http://www.gov.cn/xinwen/2022-01/11/content_5667669.htm, 2022.
    中华人民共和国生态环境部&国家统计局及农村农业部. 第二次全国污染源普查公报[EB/OL]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk01/202006/W020200610353985963290.pdf, 2020.

    Ministry of Ecology and Environment, PRC & National Bureau of Statistics & Ministry of Rural Agriculture. Bulletin of the second national census of pollution sources[EB/OL]. https://www.mee.gov.cn/xxgk2018/xxgk/xxgk01/202006/W020200610353985963290.pdf, 2020.
    ZHOU Yong, GAO Chao, GUO Yongcai. UV assisted ultrasensitive trace NO2 gas sensing based on few-layer MoS2 nanosheet–ZnO nanowire heterojunctions at room temperature[J]. Journal of Materials Chemistry A,2018,6(22):10286-10296. doi: 10.1039/C8TA02679C
    ZHOU Yong, LIU Guoqing, ZHU Xiangyi, et al. Ultrasensitive NO2 gas sensing based on rGO/MoS2 nanocomposite film at low temperature[J]. Sensors and Actuators B:Chemical,2017,251:280-290. doi: 10.1016/j.snb.2017.05.060
    AFOLARANMI S O, RAMIS F B, MARTINEZ L J L. Technology review: prototyping platforms for monitoring ambient conditions[J]. International Journal of Environmental Health Research,2018,28(3):253-279. doi: 10.1080/09603123.2018.1468423
    STOCKWELL C E, KUPC A, WITKOWSKI B, et al. Characterization of a catalyst-based conversion technique to measure total particulate nitrogen and organic carbon and comparison to a particle mass measurement instrument[J]. Atmospheric Measurement Techniques,2018,11(5):2749-2768. doi: 10.5194/amt-11-2749-2018
    MIRONENKO V R, KURITSYN Y A, LIGER V V, et al. Data processing algorithm for diagnostics of combustion using diode laser absorption spectrometry[J]. Applied Spectroscopy,2018,72(2):199-208. doi: 10.1177/0003702817732252
    QU Z, WERHAHN O, EBERT V. Thermal boundary layer effects on line-of-sight tunable diode laser absorption spectroscopy (TDLAS) gas concentration measurements[J]. Applied Spectroscopy,2018,72(6):853-862. doi: 10.1177/0003702817752112
    曲奉东. 基于纳米尺度金属氧化物异质结构的气体传感器的研究[D]. 吉林: 吉林大学, 2020.

    QU Fengdong. Research on gas sensors based on nanoscale metal oxide heterostructures[D]. Jilin: Jilin University, 2020.
    DINH T, KIM D, AHN J, et al. A potential approach to compensate the gas Interference for the analysis of NO by a non-dispersive infrared technique[J]. Analytical Chemistry,2020,92(18):12152-12159. doi: 10.1021/acs.analchem.0c00471
    SUN W Y, ZENG Y, LIU Q W. Cross-interference correction and simultaneous multi-gas analysis based on infrared absorption[J]. Chinese Physics B,2012,21(9):168-175.
    WANG Hairong, ZHANG Wei, YOU Liudong, et al. Back propagation neural network model for temperature and humidity compensation of a non dispersive infrared methane sensor[J]. Instrumentation science & technology,2013,41(6):608-618.
    GUO Yuchen, QIU Xuanbing, LI Ning, et al. A portable laser-based sensor for detecting H2S in domestic natural gas[J]. Infrared Physics & Technology,2020,105:103153.
    HEDLEY K J, SHEPSON P B, BARRFFI L, et al. An evaluation of integrating techniques for measuring atmospheric nitrogen dioxide[J]. International Journal of Environmental Analytical Chemistry,1994,54(3):167-181. doi: 10.1080/03067319408034087
    LI Jingsong, YU Benli, FISCHER H. Wavelet transform based on the optimal wavelet pairs for tunable diode laser absorption spectroscopy signal processing[J]. Applied Spectroscopy,2015,69(4):496-506. doi: 10.1366/14-07629
    MAURELLIS A N, LANG R, VAN D Z. A new DOAS parameterization for retrieval of trace gases with highly‐structured absorption spectra[J]. Geophysical Research Letters,2000,27(24):4069-4072. doi: 10.1029/2000GL011825
    WANG H S, ZHANG Y G, WU S H, et al. Using broadband absorption spectroscopy to measure concentration of sulfur dioxide[J]. Applied Physics B,2010,100(3):637-641. doi: 10.1007/s00340-010-4151-2
    XU Feng, ZHANG Yungang, SOMESFALEAN G, et al. Broadband spectroscopic sensor for real-time monitoring of industrial SO2 emissions[J]. Applied Optics,2007,46(13):2503-2506. doi: 10.1364/AO.46.002503
    ZHAO Yu, WANG Xianpei, DAI Dangdang, et al. Partial discharge early-warning through ultraviolet spectroscopic detection of SO2[J]. Measurement Science and Technology,2014,25(3):035002. doi: 10.1088/0957-0233/25/3/035002
    吕传明. 基于 DOAS 烟气在线监测系统的应用研究[D]. 天津: 天津大学, 2013.

    LYU Chuanming. Research on the application of continuous emission monitoring systems based on DOAS [D]. Tianjin: Tianjin University, 2013.
    王艳萍, 郭永彩, 凡凤莲, 等. 低浓度 NO 和 SO2 混合气体的测量方法研究[J]. 中国测试,2018,44(11):56-60. doi: 10.11857/j.issn.1674-5124.2018.11.010

    WANG Yanping, GUO Yongcai, FAN Fenglian, et al. Research on measure method of low concentration NO and SO2 gas mixtures[J]. China Measurement & Test,2018,44(11):56-60. doi: 10.11857/j.issn.1674-5124.2018.11.010
    PENG Bo, ZHOU Yong, LIU Guoqing, et al. An ultra-sensitive detection system for sulfur dioxide and nitric oxide based on improved differential optical absorption spectroscopy method[J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy,2020,233:118169. doi: 10.1016/j.saa.2020.118169
    周斌, 刘文清, 齐峰, 等. 差分吸收光谱法测量大气污染的浓度反演方法研究[J]. 物理学报,2001(9):1818-1823. doi: 10.3321/j.issn:1000-3290.2001.09.036

    ZHOU Bin, LIU Wenqing, QI Feng, et al. Research on concentration inversion method for air pollution measurement by differential absorption spectrometry[J]. Acta Physica Sinica,2001(9):1818-1823. doi: 10.3321/j.issn:1000-3290.2001.09.036
    刘新元, 谢柏青, 戴远东, 等. 射频SQUID心磁图数据自适应滤波研究[J]. 物理学报,2005(4):1937-1942. doi: 10.3321/j.issn:1000-3290.2005.04.085

    LIU Xinyuan, XIE Baiqing, DAI Yuandong, et al. Research on adaptive filtering of RF SQUID magnetocardiogram data[J]. Acta Physica Sinica,2005(4):1937-1942. doi: 10.3321/j.issn:1000-3290.2005.04.085
    孟晋丽, 傅有光, 陈翼, 等. 基于自适应滤波的雷达目标-干扰分离技术[J]. 现代雷达,2015,37(4):39-42. doi: 10.3969/j.issn.1004-7859.2015.04.009

    MENG Jinli, FU Youguang, CHEN Yi, et al. Radar target-interference separation technology based on adaptive filtering[J]. Modern Radar,2015,37(4):39-42. doi: 10.3969/j.issn.1004-7859.2015.04.009
    高鹰, 谢胜利. 一种变步长LMS自适应滤波算法及分析[J]. 电子学报,2001(8):1094-1097. doi: 10.3321/j.issn:0372-2112.2001.08.023

    GAO Ying, XIE Shengli. A variable step size LMS adaptive filtering algorithm and analysis[J]. Acta Electronica Sinica,2001(8):1094-1097. doi: 10.3321/j.issn:0372-2112.2001.08.023
    靳翼, 邵怀宗. 一种新的变步长LMS自适应滤波算法及其仿真[J]. 信号处理,2010,26(9):1385-1388. doi: 10.3969/j.issn.1003-0530.2010.09.018

    JIN Yi, SHAO Huaizong. A new variable-step LMS adaptive filtering algorithm and its simulation[J]. Journal of Signal Processing,2010,26(9):1385-1388. doi: 10.3969/j.issn.1003-0530.2010.09.018
    程学珍, 徐景东, 卫阿盈, 等. RLS自适应滤波在信号消噪中的应用[J]. 测试科学与仪器,2014,5(1):32-36.

    CHENG Xuezhen, XU Jingdong, WEI Aying, et al. Application of RLS adaptive filtering in signal denoising[J]. Journal of Measurement Science and Instrumentation,2014,5(1):32-36.
    马国栋, 阎树田, 贺成柱, 等. 基于LMS算法与RLS算法自适应滤波及仿真分析[J]. 电子设计工程,2014,22(6):43-45. doi: 10.3969/j.issn.1674-6236.2014.06.014

    MA Guodong, YAN Shutian, HE Chengzhu, et al. Adaptive filtering and simulation analysis based on LMS algorithm and RLS algorithm[J]. Electronic Design Engineering,2014,22(6):43-45. doi: 10.3969/j.issn.1674-6236.2014.06.014
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Article views (128) PDF downloads(15) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint