Self-healing FBG sensor network fault-detection based on a multi-class SVM algorithm.
Opt Express
; 31(25): 41313-41325, 2023 Dec 04.
Article
en En
| MEDLINE
| ID: mdl-38087533
ABSTRACT
We propose a three-layer ring architecture with enhanced reconfigurable capabilities for fiber Bragg grating (FBG) sensor networks. The proposed network is capable of self-healing when three fiber links fail. In addition to self-healing, soft faults in the FBG sensors can be detected using a multi-classification support vector machine (multi-class SVM) algorithm. The detection accuracy reached 99%. Additionally, we used an artificial neural network (ANN) reliability estimation model to estimate the reliability of the FBG self-healing network. The results show that the ANN reliability analysis model can accurately estimate the reliability of the architecture at a reasonable cost.
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1
Colección:
01-internacional
Banco de datos:
MEDLINE
Idioma:
En
Revista:
Opt Express
Asunto de la revista:
OFTALMOLOGIA
Año:
2023
Tipo del documento:
Article