no code implementations • 9 Oct 2023 • Daniel R. Clarkson, Lawrence A. Bull, Tina A. Dardeno, Chandula T. Wickramarachchi, Elizabeth J. Cross, Timothy J. Rogers, Keith Worden, Nikolaos Dervilis, Aidan J. Hughes
At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental costs.
no code implementations • 15 May 2023 • Lawrence A. Bull, Matthew R. Jones, Elizabeth J. Cross, Andrew Duncan, Mark Girolami
Most interestingly, domain expertise and knowledge of the underlying physics can be encoded in the model at the system, subgroup, or population level.
1 code implementation • 15 Jun 2021 • Sikai Zhang, Tingna Wang, Keith Worden, Elizabeth J. Cross
The supporting theorems developed for the feature selection method are fundamental to the understanding of the canonical correlation analysis.
no code implementations • 2 Mar 2021 • Lawrence A. Bull, Paul Gardner, Timothy J. Rogers, Elizabeth J. Cross, Nikolaos Dervilis, Keith Worden
In data-driven SHM, the signals recorded from systems in operation can be noisy and incomplete.
no code implementations • 25 Jan 2021 • Kartik Chandrasekhar, Nevena Stevanovic, Elizabeth J. Cross, Nikolaos Dervilis, Keith Worden
The methodology takes advantage of the fact that the blades on a turbine are nominally identical in structural properties and encounter the same environmental and operational variables (EOVs).
no code implementations • 5 Jan 2021 • Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden, Elizabeth J. Cross, Robin S. Mills, Timothy J. Rogers
The use of ultrasonic guided waves to probe the materials/structures for damage continues to increase in popularity for non-destructive evaluation (NDE) and structural health monitoring (SHM).
no code implementations • 21 Dec 2020 • Matthew R. Jones, Tim J. Rogers, Keith Worden, Elizabeth J. Cross
In the field of structural health monitoring (SHM), the acquisition of acoustic emissions to localise damage sources has emerged as a popular approach.
no code implementations • 3 Dec 2020 • Rajdip Nayek, Ramon Fuentes, Keith Worden, Elizabeth J. Cross
The problem of discovering governing equations is cast as that of selecting relevant variables from a predetermined dictionary of basis variables and solved via sparse Bayesian linear regression.
Model Selection Variable Selection Methodology Systems and Control Systems and Control Applications