Semi-supervised detection of structural damage using Variational Autoencoder and a One-Class Support Vector Machine

Andrea Pollastro, Giusiana Testa, Antonio Bilotta +1

In recent years, Artificial Neural Networks (ANNs) have been introduced in Structural Health Monitoring (SHM) systems. A semi-supervised method with a data-driven approach allows t…