G. Pujol

Integrating Bayesian Uncertainty into an Explainable AI Framework for CWT-CNN Structural Damage Localization

L. E. Mujica, L. Acho, P. Buenestado, Víctor Fernández-pacheco, José Gibergans, G. Pujol, et al.

TL;DR: A novel framework that integrates Bayesian Inference into the framework of Explainable AI (XAI) techniques to provide a transparent and reliability-aware diagnostic tool for structural damage localization and demonstrates that the integration of Bayesian uncertainty effectively filters out spurious hot-spots caused by environmental fluctuations.

Precision in damage localization is critical for the safety and maintenance of engineering structures. While previous studies have utilized Convolutional Neural Networks (CNNs) paired with Continuous Wavelet Transform (CWT) scalograms of ultrasonic guided waves to regress damage…Read more