arXiv:2605.20311v1 Announce Type: new Abstract: Guided-wave structural health monitoring enables damage localization in composite plates using sparse networks of bonded piezoelectric transducers. However, inferring the spatial location of defects from pitch-catch measurements remains weakly constrained when only a limited set of damage locations is available for training. As a result, models trained to predict defect locations may perform well on seen cases but generalize poorly to unseen regions of the structure. This paper proposes WaveGraphNet, a coupled inverse--forward graph learning fram
Source: arXiv cs.LG — read the full report at the original publisher.