Denoising and robust temperature extraction for botda systems based on denoising autoencoder and DNN

Biwei Wang, Nan Guo, Liang Wang, Changyuan Yu, Chao Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Denoising autoencoder is used for denoising of the data obtained by the Brillouin optical time-domain analyzer (BOTDA) sensing system and is also used to form the deep neural networks (DNN) for robust temperature information extraction.

Original languageEnglish
Title of host publicationOptical Fiber Sensors, OFS 2018
PublisherOSA - The Optical Society
ISBN (Print)9781943580507
Publication statusPublished - 24 Sep 2018
EventOptical Fiber Sensors, OFS 2018 - Lausanne, Switzerland
Duration: 24 Sep 201828 Sep 2018

Publication series

NameOptics InfoBase Conference Papers
VolumePart F124-OFS 2018

Conference

ConferenceOptical Fiber Sensors, OFS 2018
CountrySwitzerland
CityLausanne
Period24/09/1828/09/18

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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