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Feasibility study of strain and temperature discrimination in a BOTDA system via artificial neural networks

Abstract: Automatic discrimination between strain and temperature in a Brillouin optical time domain analyzer via artificial neural networks is proposed and discussed in this paper. Using a standard monomode optical fiber as the sensing element, the ability of the proposed solution to detect the known changes that the Brillouin gain spectrum exhibits depending on the applied temperature and/or strain will be studied. Experimental results, where different simultaneous strain and temperature situations have been considered, will show the feasibility of this technique.

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Authorship: Ruiz-Lombera R., Piccolo A., Rodriguez-Cobo L., Lopez-Higuera J., Mirapeix J.,

Congress: International Conference on Optical Fiber Sensors: OFS (25ª : 2017 : Jeju, República de Corea)

Publisher: SPIE Society of Photo-Optical Instrumentation Engineers

Year of publication: 2017

No. of pages: 4

Publication type: Conference object

DOI: 10.1117/12.2265435

ISSN: 0277-786X,1996-756X

Spanish project: TEC2013-47264-C2-1-R ; TEC2016-76021-C2-2-R

Publication Url: https://doi.org/10.1117/12.2265435

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Authorship

RUBEN RUIZ LOMBERA

ARIANNA PICCOLO

LUIS RODRIGUEZ COBO

JOSE MIGUEL LOPEZ HIGUERA

JESUS MARIA MIRAPEIX SERRANO

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