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Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their...
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Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 9755

Special Issue Editors

Dr. Ali Masoudi

E-Mail Website
Guest Editor
Optoelectronics Research Centre, University of Southampton, Southampton SO171BJ, UK
Interests: Distributed optical fibre vibration sensors; distributed optical fibre temperature sensors; distributed optical fibre shape sensing; optical fibre current and magnetic field sensors
Dr. Stefano Faralli

E-Mail Website
Guest Editor
Scuola Superiore Sant’Anna, Institute of Mechanical Intelligence (IIM) , I - 56124 Pisa, Italy
Interests: Optical fiber sensors; distributed temperature sensors; fiber Bragg grating sensors; distributed acoustic sensors; integrated photonic circuits; optical communications; optical amplification; optoelectronic devices
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Minghong Yang

E-Mail Website
Guest Editor
National Engineering Laboratory for Fiber Optic Sensing Technology, Wuhan University of Technology, Wuhan 430070, China
Interests: Fiber Optic Sensors; sensing materials; sensor aplications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of distributed optical fiber acoustic sensors (DASs) has seen a rapid expansion during the past 10 years. This expansion can be primarily linked to the sheer number of applications of these sensing systems: from leak detection along pipelines and the structural health monitoring of high-voltage subsea cables to monitoring geophysical activities such as earthquakes and landslides.

This Special Issue will focus on the current state-of-the-art DAS systems and their applications. We would like to invite researchers to contribute original papers as well as review articles showing: i) breakthroughs and innovative advancements in the performance of DAS systems in areas such as sensing range, strain sensitivity, frequency range, and spatial resolution; and ii) the most recent multi-disciplinary studies on the application of DAS systems in, for instance, the detection of geophysical activities, pipeline leak detection, perimeter security, and railway network monitoring.

We are look forward to receiving your contributions.

Dr. Ali Masoudi
Dr. Stefano Faralli
Prof. Dr. Minghong Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Distributed optical fiber sensors 
  • Distributed optical fiber acoustic sensors 
  • Phase sensitive optical domain reflectometry 
  • Rayleigh Scattering 
  • ……..

Published Papers (4 papers)

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Research

13 pages, 4424 KiB  
Article
Long Range Raman-Amplified Distributed Acoustic Sensor Based on Spontaneous Brillouin Scattering for Large Strain Sensing
by Shahab Bakhtiari Gorajoobi, Ali Masoudi and Gilberto Brambilla
Sensors 2022, 22(5), 2047; https://doi.org/10.3390/s22052047 - 06 Mar 2022
Cited by 2 | Viewed by 2898
Abstract
A Brillouin distributed acoustic sensor (DAS) based on optical time-domain refractometry exhibiting a maximum detectible strain of 8.7 mε and a low signal fading is developed. Strain waves with frequencies of up to 120 Hz are measured with an accuracy of 12 [...] Read more.
A Brillouin distributed acoustic sensor (DAS) based on optical time-domain refractometry exhibiting a maximum detectible strain of 8.7 mε and a low signal fading is developed. Strain waves with frequencies of up to 120 Hz are measured with an accuracy of 12 με at a sampling rate of 1.2 kHz and a spatial resolution of 4 m over a sensing range of 8.5 km. The sensing range is further extended by using a modified inline Raman amplifier configuration. Using 80 ns Raman pump pulses, the signal-to-noise ratio is improved by 3.5 dB, while the accuracy of the measurement is enhanced by a factor of 2.5 to 62 με at the far-end of a 20 km fiber. Full article
(This article belongs to the Special Issue Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their Applications)
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15 pages, 4318 KiB  
Article
Semi-Supervised Deep Learning in High-Speed Railway Track Detection Based on Distributed Fiber Acoustic Sensing
by Shulun Wang, Feng Liu and Bin Liu
Sensors 2022, 22(2), 413; https://doi.org/10.3390/s22020413 - 06 Jan 2022
Cited by 8 | Viewed by 2306
Abstract
High deployment costs, safety risks, and time delays restrict traditional track detection methods in high-speed railways. Therefore, approaches based on optical sensors have become the most remarkable strategy in terms of deployment cost and real-time performance. Owing to the large amount of data [...] Read more.
High deployment costs, safety risks, and time delays restrict traditional track detection methods in high-speed railways. Therefore, approaches based on optical sensors have become the most remarkable strategy in terms of deployment cost and real-time performance. Owing to the large amount of data obtained by sensors, it has been proven that deep learning, as a powerful data-driven approach, can perform effectively in the field of track detection. However, it is difficult and expensive to obtain labeled data from railways during operation. In this study, we used a segment of a high-speed railway track as the experimental object and deployed a distributed optical fiber acoustic system (DAS). We propose a track detection method that innovatively leverages semi-supervised deep learning based on image recognition, with a particular pre-processing for the dataset and a greedy algorithm for the selection of hyper-parameters. The superiority of the method was verified in both experiments and actual applications. Full article
(This article belongs to the Special Issue Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their Applications)
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11 pages, 4392 KiB  
Communication
High SNR Φ-OTDR with Multi-Transverse Modes Heterodyne Matched-Filtering Technology
by Yifan Liu, Junqi Yang, Bingyan Wu, Bin Lu, Luwei Shuai, Zhaoyong Wang, Lei Ye, Kang Ying, Qing Ye, Ronghui Qu and Haiwen Cai
Sensors 2021, 21(22), 7460; https://doi.org/10.3390/s21227460 - 10 Nov 2021
Cited by 3 | Viewed by 1504
Abstract
Phase-sensitive optical time domain reflectometer (Φ-OTDR) has attracted attention in scientific research and industry because of its distributed dynamic linear response to external disturbances. However, the signal-to-noise ratio (SNR) of Φ-OTDR is still a limited factor by the weak Rayleigh Backscattering coefficient. Here, [...] Read more.
Phase-sensitive optical time domain reflectometer (Φ-OTDR) has attracted attention in scientific research and industry because of its distributed dynamic linear response to external disturbances. However, the signal-to-noise ratio (SNR) of Φ-OTDR is still a limited factor by the weak Rayleigh Backscattering coefficient. Here, the multi-transverse modes heterodyne matched-filtering technology is proposed to improve the system SNR. The capture efficiency and nonlinear threshold are increased with multiple transverse modes in few-mode fibers; the incident light energy is permitted to be enlarged by a wider probe pulse by using heterodyne matched-filtering without spatial resolution being deteriorated. As far as we know, this is the first time that both multi-transverse modes integration method and digital heterodyne matched filtering method have been used to improve the SNR of Φ-OTDR simultaneously. Experimental results show that the noise floor is reduced by 11.4 dB, while the target signal is kept. We believe that this proposed method will help DAS find important applications in marine acoustic detection and seismic detection. Full article
(This article belongs to the Special Issue Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their Applications)
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11 pages, 1318 KiB  
Article
Numerical Modelling of a Distributed Acoustic Sensor Based on Ultra-Low Loss-Enhanced Backscattering Fibers
by Lieke Dorine van Putten, Ali Masoudi, James Snook and Gilberto Brambilla
Sensors 2021, 21(20), 6869; https://doi.org/10.3390/s21206869 - 16 Oct 2021
Cited by 9 | Viewed by 2106
Abstract
In this study, a distributed acoustic sensor (DAS) was numerically modeled based on the non-ideal optical components with their noises and imperfections. This model is used to compare the response of DAS systems to standard single-mode fibers and ultra-low loss-enhanced backscattering (ULEB) fibers, [...] Read more.
In this study, a distributed acoustic sensor (DAS) was numerically modeled based on the non-ideal optical components with their noises and imperfections. This model is used to compare the response of DAS systems to standard single-mode fibers and ultra-low loss-enhanced backscattering (ULEB) fibers, a fiber with an array of high reflective points equally spaced along its length. It is shown that using ULEB fibers with highly reflective points improves the signal-to-noise ratio and linearity of the measurement, compared with the measurement based on standard single-mode fibers. Full article
(This article belongs to the Special Issue Recent Advances in Distributed Optical Fiber Acoustic Sensors and Their Applications)
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