87 citations · 560 across the 49 of their papers we have counts for
10 papers · 1 filter
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…
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…
On the hierarchical Bayesian modelling of frequency response functions
T. A. Dardeno, K. Worden, N. Dervilis +2
For situations that may benefit from information sharing among datasets, e.g., population-based SHM of similar structures, the hierarchical Bayesian approach provides a useful mode…
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…
VpROM: A novel Variational AutoEncoder-boosted Reduced Order Model for the treatment of parametric dependencies in nonlinear systems
Thomas Simpson, Konstantinos Vlachas, Anthony Garland +2
Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-…
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…
Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets
S. C. Bee, E. Papatheou, M Haywood-Alexander +4
There have been recent efforts to move to population-based structural health monitoring (PBSHM) systems. One area of PBSHM which has been recognised for potential development is th…
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…