| YAN Xiangyu,LI Honglian,WANG Yitong,FANG Lide,ZHANG Rongxiang.Support vector regression-based study of interference in absorption spectral lines of mixed gases[J].Optoelectronics Letters,2022,(12):743-748 |
| Support vector regression-based study of interference in absorption spectral lines of mixed gases |
| Author Name | Affiliation | | YAN Xiangyu | School of Quality and Technical Supervision, Hebei University, Baoding 071002, China
National & Local Joint Engineering Research Center of Metrology Instrument and System, Baoding 071002, China
Hebei Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding 071002, China | | LI Honglian | School of Quality and Technical Supervision, Hebei University, Baoding 071002, China
National & Local Joint Engineering Research Center of Metrology Instrument and System, Baoding 071002, China
Hebei Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding 071002, China | | WANG Yitong | School of Quality and Technical Supervision, Hebei University, Baoding 071002, China
National & Local Joint Engineering Research Center of Metrology Instrument and System, Baoding 071002, China
Hebei Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding 071002, China | | FANG Lide | School of Quality and Technical Supervision, Hebei University, Baoding 071002, China
National & Local Joint Engineering Research Center of Metrology Instrument and System, Baoding 071002, China
Hebei Key Laboratory of Energy Metering and Safety Testing Technology, Hebei University, Baoding 071002, China | | ZHANG Rongxiang | College of Physics Science and Technology, Hebei University, Baoding 071002, China |
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| Abstract: |
| When measuring the concentration of multi-component gas mixtures based on supercontinuum laser absorption spectroscopy (SCLAS), there are interferences between the absorption spectral lines. For the spectral interference problem of CO2 and CH4 at 1 432 nm, a method based on support vector regression (SVR) is proposed in this paper. The SVR model, the k-nearest neighbor (KNN) model and the least squares (LS) model are used to analyze and predict the absorption spectral data, and the prediction accuracies were 96.29%, 88.89% and 85.19%, respectively, with the highest prediction accuracy of the SVR model. The results show that the method can accurately measure the concentration of gas mixtures, realize the detection of mixed gases using a single waveband, and provide a solution to the overlapping spectral line interference of multi-component gas mixtures. |
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