Unsupervised Learning-Based Anomaly Detection for Bridge Structural Health Monitoring: Identifying Deviations from Normal Structural Behaviour

Structural Health Monitoring (SHM) of large-scale civil infrastructure is essential to ensure safety, minimise maintenance costs, and support informed decision-making. Unsupervised anomaly detection has emerged as a powerful tool for identifying deviations in structural behaviour without requiring l...

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Autors principals:	Jabez Nesackon Abraham, Minh Q. Tran, Jerusha Samuel Jayaraj, Jose C. Matos, Maria Rosa Valluzzi, Son N. Dang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-01-01
Col·lecció:	Sensors
Matèries:	SHM unsupervised learning ensemble fusion principal component analysis autoencoder anomaly detection
Accés en línia:	https://www.mdpi.com/1424-8220/26/2/561
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