基于SVM与近红外TDLAS技术的多组分痕量气体识别与检测

doi:10.3964/j.issn.1000-0593(2024)10-2909-07

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摘要：基于可调谐半导体激光吸收光谱技术(TDLAS)，采用频分多路复用(FDM)方法，研究了一种基于支持向量机(SVM)分类的近红外多组分痕量气体识别与检测系统。激光光谱技术表征气体吸收谱线时，气体在近红外波段比远红外吸收能力低，单一波段激光光谱检测气体存在吸收信号弱，各气体组分相互干扰大。为提升探测精度，精准识别气体组分并同时进行多成分检测，基于可调谐半导体激光吸收光谱技术，采用频分复用的近红外TDLAS技术，搭配SVM分类算法进行混合气体的实时检测，有效避免了各气体的交叉干扰，实现了一氧化氮NO、硫化氢H₂S、氨气NH₃、二氧化氮NO₂、乙炔C₂H₂、二氧化碳CO₂、甲烷CH₄、氯化氢HCl八种气体标志物的痕量检测。当8个激光器同时工作时，系统控制带通滤波器进行分时滤波，并将差分锁相后的二次谐波数据依次传输至上位机实时显示。识别率超过96.3%，含量平均预测准确率均高于99.6%，取得了CH₄最低检测下限为0.01 μL·L^-1的高精度检测效果，NO₂为0.05 μL·L^-1、C₂H₂为0.03 μL·L^-1，其余气体检测下限均小于5 μL·L^-1。对系统多通道检测进行抗干扰和检测下限分析，验证系统稳定工作时实现混合气体的高精度浓度检测。采用分布反馈激光器驱动和锁相放大器与数据处理的SVM算法模型结合，实现近红外TDLAS技术的多组分痕量气体识别与检测，可满足微量气体痕量级检测，对将来进行超低浓度混合气体探测有着非常重要的意义。

关键词：可调谐半导体激光吸收光谱；频分多路复用；支持向量机；混合气体探测

Abstract：Based on tunable semiconductor laser absorption spectroscopy (TDLAS) and frequency division multiplexing (FDM) method, a near-infrared multi-component trace gas identification and detection system based on support vector machine (SVM) classification was studied. When laser spectroscopy technology characterizes gas absorption spectral lines, the absorption capacity of gas in the near-infrared band is lower than that in the far-infrared band. The absorption signal of gas detected by single-band laser spectrum is weak, and each gas component interferes with each other greatly. To improve detection accuracy, accurately identify gas components and perform multi-component detection at the same time, based on tunable semiconductor laser absorption spectroscopy technology, the frequency division multiplexing near-infrared TDLAS technology method is used, and the SVM classification algorithm is used to perform the real-time detection process of mixed gases. It effectively avoids cross-interference of various gases and realizes trace detection of eight gas markers: nitric oxide NO, hydrogen sulfide H₂S, ammonia NH₃, nitrogen dioxide NO₂, acetylene C₂H₂, carbon dioxide CO₂, methane CH₄, and hydrogen chloride HCl. When eight lasers work simultaneously, the system controls the band-pass filter to perform time-sharing filtering. It sequentially transmits the second harmonic data after differential phase locking to the host computer for real-time display. The recognition rate is over 96.3%, and the average content prediction accuracy is higher than 99.6%. It has achieved high-precision detection results with the lowest detection limit of CH₄ being 0.01 μL·L^-1, NO₂ being 0.05 μL·L^-1, and C₂H₂ being 0.03 μL·L^-1, and the detection limits of other gases are below 5 μL·L^-1. Conduct anti-interference analysis and detection lower limit analysis on the multi-channel detection of the system to verify that the system can achieve high-precision concentration detection of mixed gases when the system is operating stably. This system uses a distributed feedback laser drive and lock-in amplifier combined with the SVM algorithm model of data processing to realize multi-component trace gas identification and detection of near-infrared TDLAS technology, which can meet the trace level detection of trace gases and provide ultra-low performance for the future. The detection of concentration mixed gases is of very important significance.

Key words：TDLAS; Frequency divisionmultiplexing; Support vector machines; Mixed gas detection

收稿日期: 2023-06-21 修订日期: 2023-12-14

中图分类号:

TH744

基金资助: 国家自然科学基金项目(61905116)，苏州市姑苏创新进取人才项目（ZXL2021303），江苏科技智库计划(青年)项目(JSKX24019)资助

通讯作者: 刘向 E-mail: xjlx1906@126.com

作者简介: 房孝猛，1998年生，南京信息工程大学电子与信息工程学院硕士研究生 e-mail: 20211249212@nuist.edu.cn

引用本文:

房孝猛，王华来，徐晖，黄孟强，刘向. 基于SVM与近红外TDLAS技术的多组分痕量气体识别与检测[J]. 光谱学与光谱分析, 2024, 44(10): 2909-2915.
FANG Xiao-meng, WANG Hua-lai, XU Hui, HUANG Meng-qiang, LIU Xiang. Identification and Detection of Multi-Component Trace Gases Based on Near-Infrared TDLAS Technology Based on SVM. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(10): 2909-2915.

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https://www.gpxygpfx.com/CN/10.3964/j.issn.1000-0593(2024)10-2909-07 或 https://www.gpxygpfx.com/CN/Y2024/V44/I10/2909