A Model-Assisted Probability of Detection Framework for Optical Fiber Sensors

Journal Article (2023)
Author(s)

F. Falcetelli (University of Bologna)

N. Yue (TU Delft - Structural Integrity & Composites)

Leonardo Rossi (IMM Institute)

Gabriele Bolognini (IMM Institute)

Filippo Bastianini (SOCOTEC Photonics)

D. Zarouchas (TU Delft - Structural Integrity & Composites)

Raffaella Sante (University of Bologna)

Research Group
Structural Integrity & Composites
Copyright
© 2023 F. Falcetelli, N. Yue, Leonardo Rossi, Gabriele Bolognini, Filippo Bastianini, D. Zarouchas, Raffaella Di Sante
DOI related publication
https://doi.org/10.3390/s23104813
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 F. Falcetelli, N. Yue, Leonardo Rossi, Gabriele Bolognini, Filippo Bastianini, D. Zarouchas, Raffaella Di Sante
Research Group
Structural Integrity & Composites
Issue number
10
Volume number
23
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Abstract

Optical fiber sensors (OFSs) represent an efficient sensing solution in various structural health monitoring (SHM) applications. However, a well-defined methodology is still missing to quantify their damage detection performance, preventing their certification and full deployment in SHM. In a recent study, the authors proposed an experimental methodology to qualify distributed OFSs using the concept of probability of detection (POD). Nevertheless, POD curves require considerable testing, which is often not feasible. This study takes a step forward, presenting a model-assisted POD (MAPOD) approach for the first time applied to distributed OFSs (DOFSs). The new MAPOD framework applied to DOFSs is validated through previous experimental results, considering the mode I delamination monitoring of a double-cantilever beam (DCB) specimen under quasi-static loading conditions. The results show how strain transfer, loading conditions, human factors, interrogator resolution, and noise can alter the damage detection capabilities of DOFSs. This MAPOD approach represents a tool to study the effects of varying environmental and operational conditions on SHM systems based on DOFSs and for the design optimization of the monitoring system.