most citedQuantifying the value of information transfer in population-based SHM

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Quantifying the value of positive transfer: An experimental case study

Aidan J. Hughes, Giulia Delo, Jack Poole +2

In traditional approaches to structural health monitoring, challenges often arise associated with the availability of labelled data. Population-based structural health monitoring s…

cs.LG20231 cited

Quantifying the value of information transfer in population-based SHM

Aidan J. Hughes, Jack Poole, Nikolaos Dervilis +2

Population-based structural health monitoring (PBSHM), seeks to address some of the limitations associated with data scarcity that arise in traditional SHM. A tenet of the populati…

cs.LG2023

Sharing Information Between Machine Tools to Improve Surface Finish Forecasting

Daniel R. Clarkson, Lawrence A. Bull, Tina A. Dardeno +6

At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental cos…

cs.LG2023

A decision framework for selecting information-transfer strategies in population-based SHM

Aidan J. Hughes, Jack Poole, Nikolaos Dervilis +2

Decision-support for the operation and maintenance of structures provides significant motivation for the development and implementation of structural health monitoring (SHM) system…

cs.AI2023

Towards risk-informed PBSHM: Populations as hierarchical systems

Aidan J. Hughes, Paul Gardner, Keith Worden

The prospect of informed and optimal decision-making regarding the operation and maintenance (O&M) of structures provides impetus to the development of structural health monitoring…