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
    PublisherOptical Society of America (OSA)
    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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