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Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method

A curvelet denoising method has been proposed to reduce the time domain noise to improve the detection performance in the distributed fiber vibration sensing system based on phase-sensitive optical time domain reflectometry. The raw Rayleigh backscattering traces are regarded as a gray image and the...

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Detalles Bibliográficos
Autores principales: Qin, Zengguang, Chen, Hui, Chang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492711/
https://www.ncbi.nlm.nih.gov/pubmed/28613241
http://dx.doi.org/10.3390/s17061380
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author Qin, Zengguang
Chen, Hui
Chang, Jun
author_facet Qin, Zengguang
Chen, Hui
Chang, Jun
author_sort Qin, Zengguang
collection PubMed
description A curvelet denoising method has been proposed to reduce the time domain noise to improve the detection performance in the distributed fiber vibration sensing system based on phase-sensitive optical time domain reflectometry. The raw Rayleigh backscattering traces are regarded as a gray image and the random noise can be eliminated by the curvelet transform; hence, the amplitude difference induced by the external vibration can be extracted. The detection of a vibration event with 10 m spatial resolution along a 4 km single mode fiber is demonstrated. The signal-to-noise ratio (SNR) of location information for 50 Hz and 1 kHz vibration based on this new method increases to as high as 7.8 dB and 8.0 dB, respectively, compared to the conventional method, showing the remarkable denoising capability of this new approach.
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spelling pubmed-54927112017-07-03 Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method Qin, Zengguang Chen, Hui Chang, Jun Sensors (Basel) Article A curvelet denoising method has been proposed to reduce the time domain noise to improve the detection performance in the distributed fiber vibration sensing system based on phase-sensitive optical time domain reflectometry. The raw Rayleigh backscattering traces are regarded as a gray image and the random noise can be eliminated by the curvelet transform; hence, the amplitude difference induced by the external vibration can be extracted. The detection of a vibration event with 10 m spatial resolution along a 4 km single mode fiber is demonstrated. The signal-to-noise ratio (SNR) of location information for 50 Hz and 1 kHz vibration based on this new method increases to as high as 7.8 dB and 8.0 dB, respectively, compared to the conventional method, showing the remarkable denoising capability of this new approach. MDPI 2017-06-14 /pmc/articles/PMC5492711/ /pubmed/28613241 http://dx.doi.org/10.3390/s17061380 Text en © 2017 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
Qin, Zengguang
Chen, Hui
Chang, Jun
Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title_full Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title_fullStr Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title_full_unstemmed Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title_short Detection Performance Improvement of Distributed Vibration Sensor Based on Curvelet Denoising Method
title_sort detection performance improvement of distributed vibration sensor based on curvelet denoising method
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492711/
https://www.ncbi.nlm.nih.gov/pubmed/28613241
http://dx.doi.org/10.3390/s17061380
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