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Dual-Channel Mapping–Gas Column Concentration Inversion Method Based on Multispectral Imaging.

Authors :
Shi, Ninghao
Zhao, Yingze
Zhao, Baixuan
Zheng, Kaifeng
Chen, Yupeng
Qin, Yuxin
Wang, Weibiao
Lv, Jinguang
Liang, Jingqiu
Source :
Applied Sciences (2076-3417); Apr2024, Vol. 14 Issue 8, p3139, 17p
Publication Year :
2024

Abstract

Infrared multispectral imaging technology can achieve the long-distance, wide-ranging and fast detection of target gas, and has been widely used in the fields of dangerous-gas detection and environmental monitoring. However, due to the difficulty in acquiring background radiation as well as atmospheric disturbance and noise interference in the detection process, the quantitative detection of gas concentration has become a difficult problem to solve. Therefore, this paper proposes an inversion method for gas column concentration based on infrared multispectral imaging technology. Firstly, infrared background radiation images of the non-target gas absorption spectrum band were collected and converted into background radiation images of the target gas absorption spectrum band according to the dual-channel mapping relationship. Then, combined with the gas radiation images of the target gas absorption spectrum band, the column concentration distribution of the gas was obtained by using the measured calibration relationship between absorbance and column concentration. Experiments of gas detection in different environments were carried out, and the column concentration distribution of the target gas was inverted using this method; the results showed that the average relative error of the inversion of the gas column concentration was 4.84%, which enables the quantitative detection of gas column concentration in a complex environment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
8
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
176880950
Full Text :
https://doi.org/10.3390/app14083139