Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring

Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring

In this paper, we studied the possibility of increasing the Brillouin frequency shift (BFS) detection accuracy in distributed fibre-optic sensors by the separate and joint use of different algorithms for finding the spectral maximum: Lorentzian curve fitting (LCF, including the Levenberg–Marquardt (...

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Bibliographic Details
Main Authors: Nur Dalilla Nordin, Fairuz Abdullah, Mohd Saiful Dzulkefly Zan, Ahmad Ashrif A Bakar, Anton I. Krivosheev, Fedor L. Barkov, Yuri A. Konstantinov
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Sensors
Subjects:
Brillouin scattering
distributed fibre-optic sensors
data processing
machine learning
BFS extraction
BOTDA
Online Access:https://www.mdpi.com/1424-8220/22/7/2677

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