可编程门阵列WM-TDLAS气体检测系统设计及应用

张鑫,邱海峰,兰嘉琪,等. 可编程门阵列WM-TDLAS气体检测系统设计及应用[J]. 光电工程,2024,51(4): 240022. doi: 10.12086/oee.2024.240022
引用本文: 张鑫,邱海峰,兰嘉琪,等. 可编程门阵列WM-TDLAS气体检测系统设计及应用[J]. 光电工程,2024,51(4): 240022. doi: 10.12086/oee.2024.240022
Zhang X, Qiu H F, Lan J Q, et al. Programmable gate array WM-TDLAS gas detection system design and application[J]. Opto-Electron Eng, 2024, 51(4): 240022. doi: 10.12086/oee.2024.240022
Citation: Zhang X, Qiu H F, Lan J Q, et al. Programmable gate array WM-TDLAS gas detection system design and application[J]. Opto-Electron Eng, 2024, 51(4): 240022. doi: 10.12086/oee.2024.240022

可编程门阵列WM-TDLAS气体检测系统设计及应用

  • 基金项目:
    吉林省教育厅科学技术研究项目(JJKH20240916)
详细信息
    作者简介:
    通讯作者: 张贺,zhanghe@cust.edu.cn
  • 中图分类号: O433

Programmable gate array WM-TDLAS gas detection system design and application

  • Fund Project: Project supported by Science and Technology Research Project of Jilin Provincial Department of Education (JJKH20240916)
More Information
  • 本文基于可编程逻辑门阵列(field programmable gate array,FPGA)快速处理数字信号及多线程优势,结合波长调制可调谐半导体激光吸收光谱(WM-TDLAS)技术,研制可编程门阵列WM-TDLAS二氧化碳浓度检测系统。根据应用功能需求,利用FPGA芯片的逻辑门阵列可编程特性,设计了具备信号采集及调制、谐波解调功能的数字化锁相放大器(digital lock-in amplifier,DLIA)。为验证其性能进行谐波提取测试、Q值、抗噪声实验,结果表明目标频率提取线性度达99.99%,Q值可达45。在对不同信噪比信号进行谐波提取实验中,当信噪比为43 dB时,均值最大相对误差仅为0.91%。采用中心波长1572 nm分布式反馈激光器作为光源,覆盖选定的6360 cm−1处吸收线,密集多通气体吸收池有效光程14 m,开展了气体浓度检测实验。系统检测浓度与二次谐波幅值拟合线性度为99.982%,通过提升扫描波长频率,系统可在0.1 s获取浓度值。艾伦(Allan)方差结果表明,当积分时间为44 s时,系统的检测下限为1.86 ppm。实验结果表明,该可编程门阵列WM-TDLAS检测系统具有检测精度高、响应速度快、稳定性强和小型化的特点,可用于实际应用中浓度实时监测。

  • Overview: In view of the above situation, this paper designs a digital lock-in amplifier (DLIA) with high-frequency, long-bit-wide signal acquisition, signal modulation, and harmonic demodulation functions based on FPGA, and applies it to the carbon dioxide (CO2) concentration detection system of WM-TDLAS technology. For the concentration detection system, the hardware parameters of the lock-in amplifier and the key data processing algorithms were optimized. 1) The high-low-pass cooperation scheme is used to filter out the low-frequency clutter signal in the input data to improve the signal-to-noise ratio of the system. To reduce resource consumption and optimize system performance, a Cascaded Integeator-Comb Filter (CIC) filter is designed to perform downsampling of signals with a high sampling rate and reduce the required order of low-pass filter to achieve a lower cut-off frequency. 2) Direct Digital Frequency Synthesis (DDS) technology based on external input clocks is introduced to generate high-frequency synchronous clock reference signals, which can reduce the distortion and harmonic peak jitter caused by clock offset jitter in non-homologous digital systems. 3) The FPGA generates the laser scan signal required for wavelength modulation and the high-frequency clock required for the analog signal acquisition circuit, simplifying the peripheral circuit. This paper designs a digital quadrature lock-in amplifier based on programmable logic gate array (FPGA) programmable features. Harmonic signal demodulation is realized, and the frequency of the high-frequency laser modulation signal can be tuned. The quadrature lock-in amplifier can effectively extract the weak signal in the background noise, through the different signal-to-noise ratio of the signal to be measured under the harmonic extraction and Q value experiments. The signal-to-noise ratio of the signal under test is 43 dB with a maximum error of only 0.91%, and the Q value is 45, indicating that the lock-in amplifier has good frequency response and noise immunity. To test the performance of the designed digital quadrature phase locker in the WM-TDLAS detection, build based on the WM-TDLAS carbon dioxide experimental system to carry out the concentration detection, stability, and response time test, the amplitude of the harmonic signal extracted by the lock-in amplifier and the CO2 concentration has a good linear relationship (R2 = 0.99982), the system acquires the concentration value of the time of 0.1 s, Allen's square indicates that the detection limit is 1.86 ppm. The experimental results show that the WM-TDLAS detection system based on FPGA digital lock-in amplifier has the advantages of digital signal modulatability, high detection sensitivity, and strong noise immunity, and can be used for real-time monitoring of concentration in practical applications.

  • 加载中
  • 图 1  正交锁相原理框图

    Figure 1.  Quadrature phase lock-in principle block diagram

    图 2  可编程门阵列WM-TDLAS二氧化碳浓度检测系统结构

    Figure 2.  Structure of the FPGA-based WM-TDLAS CO2 concentration detection system

    图 3  FPGA内部逻辑结构框图

    Figure 3.  Block diagram of FPGA internal logic structure

    图 4  检测系统线性度实验。(a)正弦信号振幅提取结果;(b)提取振幅与实际值的线性拟合

    Figure 4.  Detection system linearity experiment. (a) Amplitude extraction result of sinusoidal signal; (b) Linear fitting of extracted amplitude with actual value

    图 5  抗噪声及Q值实验。(a)不同信噪比谐波提取结果;(b) DLIA频幅响应

    Figure 5.  Anti-noise and Q-value experiment. (a) Harmonic extraction results with different signal-to-noise ratio; (b) Frequency amplitude response of DLIA

    图 6  CO2浓度检测实验平台

    Figure 6.  Experimental platform for CO2 concentration detection

    图 7  二氧化碳浓度检测实验结果。(a)二次谐波波形图;(b)二氧化碳浓度反演曲线

    Figure 7.  Experimental results of carbon dioxide concentration detection. (a) Second harmonic waveforms; (b) Carbon dioxide concentration inversion curve

    图 8  二氧化碳检测系统响应时间测试

    Figure 8.  Response time test of carbon dioxide detection system

    图 9  系统稳定性实验。(a) 二氧化碳浓度波动;(b) Allan方差

    Figure 9.  System stability experiment. (a) Carbon dioxide concentration fluctuates; (b) Allan variance

    表 1  锁相放大器体积对比 (L:长;W:宽;H:高)

    Table 1.  Volume comparison of lock-in amplifier (L: Length; W: Width; H: Height)

    TypeL×W×H/cmVolume/cm3
    OE102244.8×47.5×13.328302
    MFIA28.3×23.2×10.26696
    LIA-BVD18×10×1.5270
    DLIA12.6×8.5×1.5160
    下载: 导出CSV
  • [1]

    朱丽伟, 马文广, 胡晋, 等. 近红外光谱技术检测种子质量的应用研究进展[J]. 光谱学与光谱分析, 2015, 35(2): 346−349. doi: 10.3964/j.issn.1000-0593(2015)02-0346-04

    Zhu L W, Ma W G, Hu J, et al. Advances of NIR spectroscopy technology applied in seed quality detection[J]. Spectrosc Spect Anal, 2015, 35(2): 346−349. doi: 10.3964/j.issn.1000-0593(2015)02-0346-04

    [2]

    张志荣, 孙鹏帅, 庞涛, 等. 激光吸收光谱技术在工业生产过程及安全预警标识性气体监测中的应用[J]. 光学 精密工程, 2018, 26(8): 1925−1937. doi: 10.3788/OPE.20182608.1925

    Zhang Z R, Sun P S, Pang T, et al. Application of laser absorption spectroscopy for identification gases in industrial production processes and early safety warning[J]. Opt Precision Eng, 2018, 26(8): 1925−1937. doi: 10.3788/OPE.20182608.1925

    [3]

    赵明富, 唐平, 汤斌, 等. 基于小波变换的压缩感知理论对水质检测紫外-可见光谱数据的去噪研究[J]. 光谱学与光谱分析, 2018, 38(3): 844−850. doi: 10.3964/j.issn.1000-0593(2018)03-0844-07

    Zhao M F, Tang P, Tang B, et al. Research on denoising of UV-vis spectral data for water quality detection with compressed sensing theory based on wavelet transform[J]. Spectrosc Spect Anal, 2018, 38(3): 844−850. doi: 10.3964/j.issn.1000-0593(2018)03-0844-07

    [4]

    孙利群, 邹明丽, 王旋. 可调谐半导体激光吸收光谱法在呼吸诊断中的应用[J]. 中国激光, 2021, 48(15): 1511001. doi: 10.3788/CJL202148.1511001

    Sun L Q, Zou M L, Wang X. Application of tunable diode laser absorption spectroscopy in breath diagnosis[J]. Chin J Lasers, 2021, 48(15): 1511001. doi: 10.3788/CJL202148.1511001

    [5]

    郭忠凯, 李永刚, 于博丞, 等. 锁相放大器的研究进展[J]. 物理学报, 2023, 72(22): 224206. doi: 10.7498/aps.72.20230579

    Guo Z K, Li Y G, Yu B C, et al. Research progress of lock-in amplifiers[J]. Acta Phys Sin, 2023, 72(22): 224206. doi: 10.7498/aps.72.20230579

    [6]

    何俊峰, 阚瑞峰, 许振宇, 等. 可调谐二极管激光吸收光谱氧气测量中的导数光谱处理与浓度反演算法研究[J]. 光学学报, 2014, 34(4): 0430003. doi: 10.3788/AOS201434.0430003

    He J F, Kan R F, Xu Z Y, et al. Derivative spectrum and concentration inversion algorithm of tunable diode laser absorption spectroscopy oxygen measurement[J]. Acta Opt Sin, 2014, 34(4): 0430003. doi: 10.3788/AOS201434.0430003

    [7]

    Tao L, Sun K, Khan M A, et al. Compact and portable open-path sensor for simultaneous measurements of atmospheric N2O and CO using a quantum cascade laser[J]. Opt Express, 2012, 20(27): 28106−28118. doi: 10.1364/OE.20.028106

    [8]

    Deng B T, Sima C, Xiao Y F, et al. Modified laser scanning technique in wavelength modulation spectroscopy for advanced TDLAS gas sensing[J]. Opt Lasers Eng, 2021, 151: 106906. doi: 10.1016/j.optlaseng.2021.106906

    [9]

    Liang W, Wei G, He A, et al. A novel wavelength modulation spectroscopy in TDLAS[J]. Inf Phys Tech, 2021, 114: 103661. doi: 10.1016/j.infrared.2021.103661

    [10]

    Bagchi S, SenGupta S, Mondal S. Development and characterization of carbonic anhydrase-based CO2 biosensor for primary diagnosis of respiratory health[J]. IEEE Sensors J, 2017, 17(5): 1384−1390. doi: 10.1109/JSEN.2017.2649686

    [11]

    Li C G, Dong L, Zheng C T, et al. Compact TDLAS based optical sensor for ppb-level ethane detection by use of a 3.34 μm room-temperature CW interband cascade laser[J]. Sens Actuators B:Chem, 2016, 232: 188−194. doi: 10.1016/j.snb.2016.03.141

    [12]

    Wang Z, Wang Q, Ching J Y L, et al. A portable low-power QEPAS-based CO2 isotope sensor using a fiber-coupled interband cascade laser[J]. Sens Actuators B:Chem, 2017, 246: 710−715. doi: 10.1016/j.snb.2017.02.133

    [13]

    聂伟, 阚瑞峰, 杨晨光, 等. 可调谐二极管激光吸收光谱技术的应用研究进展[J]. 中国激光, 2018, 45(9): 0911001. doi: 10.3788/CJL201845.0911001

    Nie W, Kan R F, Yang C G, et al. Research progress on the application of tunable diode laser absorption spectroscopy[J]. Chin J Lasers, 2018, 45(9): 0911001. doi: 10.3788/CJL201845.0911001

    [14]

    曲世敏, 王明, 李楠. 基于TDLAS-WMS的中红外痕量CH4检测仪[J]. 光谱学与光谱分析, 2016, 36(10): 3174−3178. doi: 10.3964/j.issn.1000-0593(2016)10-3174-05

    Qu S M, Wang M, Li N. Mid-infrared trace CH4 detector based on TDLAS-WMS[J]. Spectrosc Spect Anal, 2016, 36(10): 3174−3178. doi: 10.3964/j.issn.1000-0593(2016)10-3174-05

    [15]

    贾良权, 祁亨年, 胡文军, 等. 采用TDLAS技术的玉米种子活力快速无损分级检测[J]. 中国激光, 2019, 46(9): 0911002. doi: 10.3788/CJL201946.0911002

    Jia L Q, Qi X N, Hu W J, et al. Rapid nondestructive grading detection of maize seed vigor using TDLAS technique[J]. Chin J Lasers, 2019, 46(9): 0911002. doi: 10.3788/CJL201946.0911002

    [16]

    叶玮琳, 涂子涵, 肖旭鹏, 等. 基于LabVIEW的TDLAS检测系统多参数影响研究[J]. 华南理工大学学报(自然科学版), 2021, 49(6): 141−148. doi: 10.12141/j.issn.1000-565X.190940

    Ye W L, Tu Z H, Xiao X P, et al. On multi-parameter influence of TDLAS detection system based on LabVIEW[J]. J South China Univ Technol (Nat Sci Ed), 2021, 49(6): 141−148. doi: 10.12141/j.issn.1000-565X.190940

    [17]

    Huang A, Cao Z, Wang C R, et al. An FPGA-based on-chip neural network for TDLAS tomography in dynamic flames[J]. IEEE Trans Instrum Meas, 2021, 70: 4506911. doi: 10.1109/TIM.2021.3115210.

    [18]

    Tang Y N, Li S Y, Liu C, et al. Process simulation and techno-economic analysis on novel CO2 capture technologies for fluid catalytic cracking units[J]. Fuel Process Technol, 2023, 249: 107855. doi: 10.1016/j.fuproc.2023.107855

    [19]

    Luo H J, Yang Z F, Zhuang R B, et al. Ppbv-level mid-infrared photoacoustic sensor for mouth alcohol test after consuming lychee fruits[J]. Photoacoustics, 2023, 33: 100559. doi: 10.1016/j.pacs.2023.100559

    [20]

    高彦伟, 张玉钧, 陈东, 等. 基于可调谐半导体激光吸收光谱的氧气浓度测量研究[J]. 光学学报, 2016, 36(3): 0330001. doi: 10.3788/AOS201636.0330001

    Gao Y W, Zhang Y J, Chen D, et al. Measurement of oxygen concentration using tunable diode laser absorption spectroscopy[J]. Acta Opt Sin, 2016, 36(3): 0330001. doi: 10.3788/AOS201636.0330001

    [21]

    Lee J, Kim T W, Lee C, et al. Integrated approach to evaluating the effect of indoor CO2 concentration on human cognitive performance and neural responses in office environment[J]. J Manage Eng, 2022, 38(1): 04021085. doi: 10.1061/(ASCE)ME.1943-5479.0000993

    [22]

    贾军伟, 李伟, 柴昊, 等. 基于TDLAS的气体检测技术算法[J]. 红外与激光工程, 2019, 48(5): 202−208.

    Jia J W, Li W, Chai H, et al. Gas detection technology algorithm based on TDLAS[J]. Infrared Laser Eng, 2019, 48(5): 202−208.

    [23]

    Zhang Z W, Chang J, Sun J C, et al. Dual-beam antiphase method to improve the WMS measurement limit in long-distance methane detection[J]. Appl Opt, 2020, 59(27): 8217−8223. doi: 10.1364/AO.402774

    [24]

    Ye W L, He L F, Xia Z K, et al. Miniaturized methane detection system based on photoacoustic spectroscopy[J]. Microw Opt Technol Lett, 2023, 65(5): 1421−1426. doi: 10.1002/mop.33611

    [25]

    Meng X R, Chang H Q, Wang X Q. Methane concentration prediction method based on deep learning and classical time series analysis[J]. Energies, 2022, 15(6): 2262. doi: 10.3390/en15062262

  • 加载中

(10)

(1)

计量
  • 文章访问数:  434
  • PDF下载数:  133
  • 施引文献:  0
出版历程
收稿日期:  2024-01-02
修回日期:  2024-02-27
录用日期:  2024-02-27
刊出日期:  2024-04-25

目录

/

返回文章
返回