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Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition

Phase-drift elimination is crucial to vibration recovery in the coherent detection phase-sensitive optical time domain reflectometry system. The phase drift drives the whole phase signal fluctuation as a baseline, and its negative effect is obvious when the detection time is long. In this paper, emp...

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Detalles Bibliográficos
Autores principales: Lv, Yuejuan, Wang, Pengfei, Wang, Yu, Liu, Xin, Bai, Qing, Li, Peihong, Zhang, Hongjuan, Gao, Yan, Jin, Baoquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960885/
https://www.ncbi.nlm.nih.gov/pubmed/31817736
http://dx.doi.org/10.3390/s19245392
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author Lv, Yuejuan
Wang, Pengfei
Wang, Yu
Liu, Xin
Bai, Qing
Li, Peihong
Zhang, Hongjuan
Gao, Yan
Jin, Baoquan
author_facet Lv, Yuejuan
Wang, Pengfei
Wang, Yu
Liu, Xin
Bai, Qing
Li, Peihong
Zhang, Hongjuan
Gao, Yan
Jin, Baoquan
author_sort Lv, Yuejuan
collection PubMed
description Phase-drift elimination is crucial to vibration recovery in the coherent detection phase-sensitive optical time domain reflectometry system. The phase drift drives the whole phase signal fluctuation as a baseline, and its negative effect is obvious when the detection time is long. In this paper, empirical mode decomposition (EMD) is presented to extract and eliminate the phase drift adaptively. It decomposes the signal by utilizing the characteristic time scale of the data, and the baseline is eventually obtained. It is validated by theory and experiment that the phase drift deteriorates seriously when the length of the vibration region increases. In an experiment, the phase drift was eliminated under the conditions of different vibration frequencies of 1 Hz, 5 Hz, and 10 Hz. The phase drift was also eliminated with different vibration intensities. Furthermore, the linear relationship between phase and vibration intensity is demonstrated with a correlation coefficient of 99.99%. The vibrations at 0.5 Hz and 0.3 Hz were detected with signal-to-noise ratios (SNRs) of 55.58 dB and 64.44 dB. With this method, when the vibration frequency is at the level of Hz or sub-Hz, the phase drift can be eliminated. This contributes to the detection and recovery of low-frequency perturbation events in practical applications.
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spelling pubmed-69608852020-01-24 Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition Lv, Yuejuan Wang, Pengfei Wang, Yu Liu, Xin Bai, Qing Li, Peihong Zhang, Hongjuan Gao, Yan Jin, Baoquan Sensors (Basel) Article Phase-drift elimination is crucial to vibration recovery in the coherent detection phase-sensitive optical time domain reflectometry system. The phase drift drives the whole phase signal fluctuation as a baseline, and its negative effect is obvious when the detection time is long. In this paper, empirical mode decomposition (EMD) is presented to extract and eliminate the phase drift adaptively. It decomposes the signal by utilizing the characteristic time scale of the data, and the baseline is eventually obtained. It is validated by theory and experiment that the phase drift deteriorates seriously when the length of the vibration region increases. In an experiment, the phase drift was eliminated under the conditions of different vibration frequencies of 1 Hz, 5 Hz, and 10 Hz. The phase drift was also eliminated with different vibration intensities. Furthermore, the linear relationship between phase and vibration intensity is demonstrated with a correlation coefficient of 99.99%. The vibrations at 0.5 Hz and 0.3 Hz were detected with signal-to-noise ratios (SNRs) of 55.58 dB and 64.44 dB. With this method, when the vibration frequency is at the level of Hz or sub-Hz, the phase drift can be eliminated. This contributes to the detection and recovery of low-frequency perturbation events in practical applications. MDPI 2019-12-06 /pmc/articles/PMC6960885/ /pubmed/31817736 http://dx.doi.org/10.3390/s19245392 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lv, Yuejuan
Wang, Pengfei
Wang, Yu
Liu, Xin
Bai, Qing
Li, Peihong
Zhang, Hongjuan
Gao, Yan
Jin, Baoquan
Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title_full Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title_fullStr Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title_full_unstemmed Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title_short Eliminating Phase Drift for Distributed Optical Fiber Acoustic Sensing System with Empirical Mode Decomposition
title_sort eliminating phase drift for distributed optical fiber acoustic sensing system with empirical mode decomposition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960885/
https://www.ncbi.nlm.nih.gov/pubmed/31817736
http://dx.doi.org/10.3390/s19245392
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