A regional damage localization method for composite plate based on guided waves and semi-supervised generative adversarial networks
Data-driven structural health monitoring is promising for complex structures but usually requires large-scale and high-quality labeled data. In practice, damaged samples are costly to obtain and difficult to annotate accurately. To overcome these limitations, this work introduces a semi-supervised generative adversaria...