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Low latency disturbance detection using distributed optical fiber sensors
University of Brasilia, Brazil.
University of Campinas, Brazil.
RISE - Research Institutes of Sweden, ICT, Acreo.ORCID iD: 0000-0001-8058-2140
University of Campinas, Brazil.
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2017 (English)In: Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control, ICNSC 2017, 2017, p. 372-377Conference paper, Published paper (Refereed)
Abstract [en]

Distributed optical fiber sensors based on phase-sensitive optical time domain reflectometry (Φ-OTDR) are feasible options to detect perturbations in kilometric security perimeters or mechanical structures. This technique takes advantage of electromagnetic interference immunity, small dimensions, lightweight, flexibility, and capability. Moreover, this technique can be combined with dedicated hardware architectures, in order to improve its performance and reliability. This work proposes the use of parallel hardware architectures to implement real-time detecting and locating perturbations in a Φ-OTDR distributed optical fiber vibration sensor. Hardware architectures of the iterative moving average filter and the Sobel filter were mapped on field programmable gate arrays, exploring the intrinsic parallelism in order to achieve real-time requirements. A performance comparison between the proposed solutions was addressed in terms of hardware cost, latency and power consumption.

Place, publisher, year, edition, pages
2017. p. 372-377
Keywords [en]
Distributed sensors, FPGAs, Hardware architectures, Optical fiber vibration sensors, Optical time-domain reflectometer (OTDR), Electromagnetic pulse, Fiber optic sensors, Fibers, Field programmable gate arrays (FPGA), Hardware, Iterative methods, Optical fibers, Reflectometers, Ventilation exhausts, Distributed optical fiber, Distributed optical fiber sensors, Distributed sensor, Hardware architecture, Optical time domain reflectometer, Optical time domain reflectometry, Performance and reliabilities, Vibration sensors, Time domain analysis
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-32499DOI: 10.1109/ICNSC.2017.8000121Scopus ID: 2-s2.0-85028506370ISBN: 9781509044283 (print)OAI: oai:DiVA.org:ri-32499DiVA, id: diva2:1155824
Conference
14th IEEE International Conference on Networking, Sensing and Control, ICNSC 2017, 16 May 2017 through 18 May 2017
Available from: 2017-11-09 Created: 2017-11-09 Last updated: 2018-08-15Bibliographically approved

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Margulis, Walter

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
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