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ShanghaiTech University Knowledge Management System
Highly sensitive mid-infrared methane remote sensor using a deep neural network filter | |
2024-03-25 | |
发表期刊 | OPTICS EXPRESS (IF:3.2[JCR-2023],3.4[5-Year]) |
ISSN | 1094-4087 |
EISSN | 1094-4087 |
卷号 | 32期号:7页码:11849-11862 |
发表状态 | 已发表 |
DOI | 10.1364/OE.520245 |
摘要 | A novel mid-infrared methane remote sensor integrated on a movable platform based on a 3.291-µm interband cascade laser (ICL) and wavelength modulation spectroscopy (WMS) is proposed. A transmitting-receiving coaxial, visualized optical layout is employed to minimize laser energy loss. Using a hollow retro-reflector remotely deployed as a cooperative target, the atmospheric average methane concentration over a 100-meter optical range is measured with high sensitivity. A deep neural network (DNN) filter is used for second harmonic (2f) signal denoising to compensate for the performance shortcomings of conventional filtering. Allan deviation analysis indicated that after applying the DNN filter, the limit of detection (LOD) of methane was 86.62 ppb with an average time of 1 s, decreasing to 12.03 ppb with an average time of 229 s, which is a significant promotion compared to similar work reported. The high sensitivity and stability of the proposed sensor are shown through a 24-hour continuous monitoring experiment of atmospheric methane conducted outdoors, providing a new solution for high-sensitivity remote sensing of atmospheric methane. © 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement. |
关键词 | Atmospheric chemistry Deep neural networks Energy dissipation Infrared devices Molecular spectroscopy Optical remote sensing Quantum cascade lasers Atmospheric methanes High sensitivity Interband cascade laser Laser modulation Midinfrared Movable platforms Neural network filters Optical layouts Remote sensors Wavelength modulation spectroscopy |
URL | 查看原文 |
收录类别 | EI ; SCI |
语种 | 英语 |
资助项目 | Civil space technology pre-research of the 14-th five-years plan[D040107] ; Key basic research projects of the Basic Strengthening Program[2021-173ZD-025] |
WOS研究方向 | Optics |
WOS类目 | Optics |
WOS记录号 | WOS:001206706900001 |
出版者 | Optica Publishing Group (formerly OSA) |
EI入藏号 | 20241415838415 |
EI主题词 | Methane |
EI分类号 | 443.1 Atmospheric Properties ; 461.4 Ergonomics and Human Factors Engineering ; 525.4 Energy Losses (industrial and residential) ; 741.3 Optical Devices and Systems ; 744.1 Lasers, General ; 801.1 Chemistry, General ; 804.1 Organic Compounds |
原始文献类型 | Journal article (JA) |
引用统计 | 正在获取...
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文献类型 | 期刊论文 |
条目标识符 | https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/359874 |
专题 | 信息科学与技术学院 信息科学与技术学院_特聘教授组_王建宇组 信息科学与技术学院_硕士生 |
通讯作者 | Li, Chunlai |
作者单位 | 1.Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai; 200083, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China; 3.School of Information Science and Technology, ShanghaiTech University, Shanghai; 201210, China; 4.Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Zhejiang, Hangzhou; 310024, China |
推荐引用方式 GB/T 7714 | Wang, Senyuan,Yang, Shicheng,Zhu, Shouzheng,et al. Highly sensitive mid-infrared methane remote sensor using a deep neural network filter[J]. OPTICS EXPRESS,2024,32(7):11849-11862. |
APA | Wang, Senyuan.,Yang, Shicheng.,Zhu, Shouzheng.,Liu, Shijie.,He, Xin.,...&Wang, Jianyu.(2024).Highly sensitive mid-infrared methane remote sensor using a deep neural network filter.OPTICS EXPRESS,32(7),11849-11862. |
MLA | Wang, Senyuan,et al."Highly sensitive mid-infrared methane remote sensor using a deep neural network filter".OPTICS EXPRESS 32.7(2024):11849-11862. |
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