45 citations · 217 across the 37 of their papers we have counts for
7 papers · 1 filter
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…
Towards a population-informed approach to the definition of data-driven models for structural dynamics
G. Tsialiamanis, N. Dervilis, D. J. Wagg +1
Machine learning has affected the way in which many phenomena for various domains are modelled, one of these domains being that of structural dynamics. However, because machine-lea…
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…
When is an SHM problem a Multi-Task-Learning problem?
Sarah Bee, Lawrence Bull, Nikolas Dervilis +1
Multi-task neural networks learn tasks simultaneously to improve individual task performance. There are three mechanisms of multi-task learning (MTL) which are explored here for th…
A probabilistic approach for acoustic emission based monitoring techniques: with application to structural health monitoring
C. A. Lindley, M. R. Jones, T. J. Rogers +4
It has been demonstrated that acoustic-emission (AE), inspection of structures can offer advantages over other types of monitoring techniques in the detection of damage; namely, an…
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…
A Meta-Learning Approach to Population-Based Modelling of Structures
G. Tsialiamanis, N. Dervilis, D. J. Wagg +1
A major problem of machine-learning approaches in structural dynamics is the frequent lack of structural data. Inspired by the recently-emerging field of population-based structura…