semantic_scholare-Journal of Nondestructive Testing2026-08-01
Autoencoder-Assisted Domain Adaptation via Procrustes-Based Latent Alignment for Structural Health Monitoring
Wellington De lima nogueira, S. D. da Silva, Eloi Figueiredo
TL;DR: A framework that combines unsupervised learning and domain adaptation to enhance model transferability under limited data, reducing dependence on labeled datasets while preserving sensitivity to structural and operational changes is proposed.
Abstract: The scarcity of long-term vibration data real-world structures remains a significant barrier to the application of machine learning in structural health monitoring (SHM). Available datasets are often short, unlabeled, and affected by operational and environmental variab…