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structural health monitoring

topic1 events
papersSEP 10 04:00 UTC

WaveGraphNet couples inverse and forward graph learning for guided-wave damage localization

A research paper introduces WaveGraphNet, a graph-based approach that localizes damage in composite plates from sparse networks of piezoelectric sensors using guided waves. By jointly training inverse and forward models under physics-consistency constraints, the method aims to overcome the weak supervision that limits standard approaches when only a few sensor measurements are available.

graph-neural-networks/physics-informed/structural-monitoring/sparse-sensing