Jesús Sesé

Evaluating Transfer Learning Strategies for Neural Network-based Impact Location Model

Daniel del-Río-Velilla, Jesús Sesé, Fernando Sánchez Iglesias, Antonio Fernández López

TL;DR: This paper investigates transfer learning (TL) as a strategy to adapt a multilayer perceptron (MLP) trained on a stiffened AS4/8552 CFRP panel to ten alternative sensor layouts, simulated via controlled sensor-index permutations grouped into three families of increasing severity.

Passive impact localization using piezoelectric sensor (PZT) networks and machine learning is an established approach for structural health monitoring of composite aerospace panels. A key practical limitation is that models trained on one sensor layout fail when deployed on a str…Read more