A Neural Network Method For The BFS Extraction

We present a method for increasing the accuracy of determining the Brillouin frequency shift in a fiber strain sensor. A neural network which using the results obtained from other methods as input data and the parameters of the system is applied. The result is an additional 10% accuracy increasing,...

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Bibliographic Details
Published in2022 International Conference Laser Optics (ICLO) p. 01
Main Authors Krivosheev, A.I., Konstantinov, Yu.A., Krishtop, V.V., Turov, A.T., Barkov, F.L., Zhirnov, A.A., Garin, E.O., Pnev, A.B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 20.06.2022
Subjects
artificial neural network
BOTDA
Brillouin scattering
deformation measurements
Measurement by laser beam
Neural networks
Optical fiber networks
Optical fiber sensors
Optical variables measurement
Optics
Scattering
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Summary:We present a method for increasing the accuracy of determining the Brillouin frequency shift in a fiber strain sensor. A neural network which using the results obtained from other methods as input data and the parameters of the system is applied. The result is an additional 10% accuracy increasing, which is significant given that existing methods have already reached their limit and work at low SNR values (about 5 dB).
ISBN:1665466634
9781665466639
ISSN:2642-5580
DOI:10.1109/ICLO54117.2022.9839892