Machine learning assisted Fibre Bragg Grating based temperature sensing

Martin S.E. Djurhuus, Stefan Werzinger, Bernhard Schmauss, Anders T. Clausen, Darko Zibar

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this paper a machine learning method Gaussian process regression (GPR) is applied to directly learn the mapping between the measured spectrum and the temperature. A comparison with other conventional methods is performed and it is shown that the GPR based method gives a better performance in cases with low noise.

Original languageEnglish
Title of host publicationOptical Fiber Sensors, OFS 2018
Number of pages4
PublisherOSA - The Optical Society
Publication date1 Jan 2018
Article numberPaper ThE80
ISBN (Print)9781943580507
DOIs
Publication statusPublished - 1 Jan 2018
Event26th International Conference on Optical Fiber Sensors - SwissTech Convention Center, EPFL Campus, Lausanne, Switzerland
Duration: 24 Sep 201828 Sep 2018
https://www.osa.org/en-us/meetings/topical_meetings/26th_international_conference_on_optical_fiber_sen/

Conference

Conference26th International Conference on Optical Fiber Sensors
LocationSwissTech Convention Center, EPFL Campus
Country/TerritorySwitzerland
CityLausanne
Period24/09/201828/09/2018
Internet address

Bibliographical note

From the session: Poster Session III (ThE)

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