Damage Localization Using Fiber Bragg Grating Sensors in Self-referencing Conguration: A Numerical Study - Abhishek Patange; Farzam Omidi Moaf; Piotr Fiborek; Adityan Arumuganainar; Rohan Nandkishor Soman (Computer Assisted Methods in Engineering and Science, 2025)
This study investigates a self-referencing method for damage detection and localization using guided waves (GW) sensed by fiber Bragg grating (FBG) sensors. The research integrates advanced numerical simulations with an innovative configuration of sensors to enhance structural health monitoring (SHM). A self-referencing setup, employing FBG sensors with edge filtering method and remote bonding, enables a baseline-free damage detection approach. The methodology is validated as a proof-of-concept numerical model. The simulation framework incorporates a three-dimensional spectral element method for precise and efficient modelling of GW propagation and interactions with structural anomalies. Three different machine learning (ML) techniques are employed to detect and localize damages, demonstrating effectiveness of ML methods compared to traditional methods.