石油与天然气化工2025，Vol.54Issue(3)：130-137,8.DOI:10.3969/j.issn.1007-3426.2025.03.018
基于HITRAN数据库的高含硫气体红外光谱定量分析
Quantitative analysis of high sulfur-containing gases by infrared spectroscopy based on HITRAN database
摘要
Abstract
Objective To enhance the safety and efficiency of hazardous gas detection while minimizing operational risks,this study investigates a quantitative analysis method for high hydrogen sulfide(H2S)-containing gas mixtures based on the high-resolution transmission molecular absorption database(HITRAN database),and further validates the feasibility of its application in the fields of industrial,environmental monitoring,and public safety.Method Fourier transform infrared(FTIR)spectroscopy was employed in conjunction with support vector regression(SVR)and radial basis function(RBF)neural network models to perform quantitative analysis on gas mixtures containing H2S,CO2,and CH4.High-precision theoretical spectra data were generated using the HITRAN database,and a spectral superposition method was applied to simulate the infrared spectra of gas mixtures.The noise was added to simulate the response characteristics of FTIR instruments,making the simulated spectra closer to real detection scenarios.Result The proposed method demonstrated high efficiency and precision in the quantitative analysis of multi-component gas mixtures.The radial basis function kernel-based SVR(R-SVR)model outperformed the RBF neural network model,achieving higher detection precision.Conclusion This study provides a low-cost,efficient,and safe simulation-based validation method for detecting high H2S-containing gas mixtures.It offers reliable technical support for multi-component gas mixtures detection in practical applications and holds significant value for engineering practices.关键词
H2S/HITRAN数据库/红外光谱/定量分析/RBF神经网络/支持向量回归Key words
H2S/HITRAN database/infrared spectroscopy/quantitative analysis/RBF neural network/support vector regression引用本文复制引用
杨正刚,曾巧,奚宁凯,高进,李太福..基于HITRAN数据库的高含硫气体红外光谱定量分析[J].石油与天然气化工,2025,54(3):130-137,8.基金项目
中国石油西南油气田公司天然气净化总厂科研项目"天然气净化厂酸气主要组分在线检测技术研究"(2023-01) （2023-01）
