4 papers
Transfer learning via interpolating structures
T. A. Dardeno, A. J. Hughes, L. A. Bull +3
Despite recent advances in population-based structural health monitoring (PBSHM), knowledge transfer between highly-disparate structures (i.e., heterogeneous populations) remains a…
Active transfer learning for structural health monitoring
J. Poole, N. Dervilis, K. Worden +4
Data for training structural health monitoring (SHM) systems are often expensive and/or impractical to obtain, particularly for labelled data. Population-based SHM (PBSHM) aims to…
Physics-informed transfer learning for SHM via feature selection
J. Poole, P. Gardner, A. J. Hughes +4
Data used for training structural health monitoring (SHM) systems are expensive and often impractical to obtain, particularly labelled data. Population-based SHM presents a potenti…
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring
C. A. Lindley, N. Dervilis, K. Worden
Whenever data-based systems are employed in engineering applications, defining an optimal statistical representation is subject to the problem of model selection. This paper focuss…