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Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection

Enhancement of trace gas detectability using photoacoustic spectroscopy requires the effective suppression of strong background noise for practical applications. An upgraded infrared broadband trace gas detection configuration was investigated based on a Fourier transform infrared (FTIR) spectromete...

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Autores principales: Liu, Lixian, Huan, Huiting, Li, Wei, Mandelis, Andreas, Wang, Yafei, Zhang, Le, Zhang, Xueshi, Yin, Xukun, Wu, Yuxiang, Shao, Xiaopeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749430/
https://www.ncbi.nlm.nih.gov/pubmed/33365230
http://dx.doi.org/10.1016/j.pacs.2020.100228
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author Liu, Lixian
Huan, Huiting
Li, Wei
Mandelis, Andreas
Wang, Yafei
Zhang, Le
Zhang, Xueshi
Yin, Xukun
Wu, Yuxiang
Shao, Xiaopeng
author_facet Liu, Lixian
Huan, Huiting
Li, Wei
Mandelis, Andreas
Wang, Yafei
Zhang, Le
Zhang, Xueshi
Yin, Xukun
Wu, Yuxiang
Shao, Xiaopeng
author_sort Liu, Lixian
collection PubMed
description Enhancement of trace gas detectability using photoacoustic spectroscopy requires the effective suppression of strong background noise for practical applications. An upgraded infrared broadband trace gas detection configuration was investigated based on a Fourier transform infrared (FTIR) spectrometer equipped with specially designed T-resonators and simultaneous differential optical and photoacoustic measurement capabilities. By using acetylene and local air as appropriate samples, the detectivity of the differential photoacoustic mode was demonstrated to be far better than the pure optical approach both theoretically and experimentally, due to the effectiveness of light-correlated coherent noise suppression of non-intrinsic optical baseline signals. The wavelet domain denoising algorithm with the optimized parameters was introduced in detail to greatly improve the signal-to-noise ratio by denoising the incoherent ambient interference with respect to the differential photoacoustic measurement. The results showed enhancement of sensitivity to acetylene from 5 ppmv (original differential mode) to 806 ppbv, a fivefold improvement. With the suppression of background noise accomplished by the optimized wavelet domain denoising algorithm, the broadband differential photoacoustic trace gas detection was shown to be an effective approach for trace gas detection.
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spelling pubmed-77494302020-12-22 Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection Liu, Lixian Huan, Huiting Li, Wei Mandelis, Andreas Wang, Yafei Zhang, Le Zhang, Xueshi Yin, Xukun Wu, Yuxiang Shao, Xiaopeng Photoacoustics Research Article Enhancement of trace gas detectability using photoacoustic spectroscopy requires the effective suppression of strong background noise for practical applications. An upgraded infrared broadband trace gas detection configuration was investigated based on a Fourier transform infrared (FTIR) spectrometer equipped with specially designed T-resonators and simultaneous differential optical and photoacoustic measurement capabilities. By using acetylene and local air as appropriate samples, the detectivity of the differential photoacoustic mode was demonstrated to be far better than the pure optical approach both theoretically and experimentally, due to the effectiveness of light-correlated coherent noise suppression of non-intrinsic optical baseline signals. The wavelet domain denoising algorithm with the optimized parameters was introduced in detail to greatly improve the signal-to-noise ratio by denoising the incoherent ambient interference with respect to the differential photoacoustic measurement. The results showed enhancement of sensitivity to acetylene from 5 ppmv (original differential mode) to 806 ppbv, a fivefold improvement. With the suppression of background noise accomplished by the optimized wavelet domain denoising algorithm, the broadband differential photoacoustic trace gas detection was shown to be an effective approach for trace gas detection. Elsevier 2020-12-05 /pmc/articles/PMC7749430/ /pubmed/33365230 http://dx.doi.org/10.1016/j.pacs.2020.100228 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Liu, Lixian
Huan, Huiting
Li, Wei
Mandelis, Andreas
Wang, Yafei
Zhang, Le
Zhang, Xueshi
Yin, Xukun
Wu, Yuxiang
Shao, Xiaopeng
Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title_full Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title_fullStr Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title_full_unstemmed Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title_short Highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
title_sort highly sensitive broadband differential infrared photoacoustic spectroscopy with wavelet denoising algorithm for trace gas detection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749430/
https://www.ncbi.nlm.nih.gov/pubmed/33365230
http://dx.doi.org/10.1016/j.pacs.2020.100228
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