45 citations · 217 across the 37 of their papers we have counts for
17 papers · 1 filter
A topological analysis of cointegrated data: a Z24 Bridge case study
Tristan Gowdridge, Elizabeth Cross, Nikolaos Dervilis +1
The paper studies the topological changes from before and after cointegration, for the natural frequencies of the Z24 Bridge. The second natural frequency is known to be nonlinear…
On the application of topological data analysis: a Z24 Bridge case study
Tristan Gowdridge, Nikolaos Dervilis, Keith Worden
Topological methods are very rarely used in structural health monitoring (SHM), or indeed in structural dynamics generally, especially when considering the structure and topology o…
On topological data analysis for structural dynamics: an introduction to persistent homology
Tristan Gowdridge, Nikolaos Dervilis, Keith Worden
Topological methods can provide a way of proposing new metrics and methods of scrutinising data, that otherwise may be overlooked. In this work, a method of quantifying the shape o…
A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves
Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden +3
Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation. A key property of guided waves is the fully-define…
On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation
G. Tsialiamanis, D. Wagg, N. Dervilis +1
A major problem of structural health monitoring (SHM) has been the prognosis of damage and the definition of the remaining useful life of a structure. Both tasks depend on many par…
Mitigating sampling bias in risk-based active learning via an EM algorithm
Aidan J. Hughes, Lawrence A. Bull, Paul Gardner +2
Risk-based active learning is an approach to developing statistical classifiers for online decision-support. In this approach, data-label querying is guided according to the expect…
A generalised form for a homogeneous population of structures using an overlapping mixture of Gaussian processes
Tina A. Dardeno, Lawrence A. Bull, Nikolaos Dervilis +1
Reductions in natural frequency are often used as a damage indicator for structural health monitoring (SHM) purposes. However, fluctuations in operational and environmental conditi…
Improving decision-making via risk-based active learning: Probabilistic discriminative classifiers
Aidan J. Hughes, Paul Gardner, Lawrence A. Bull +2
Gaining the ability to make informed decisions on operation and maintenance of structures provides motivation for the implementation of structural health monitoring (SHM) systems.…
Informative Bayesian Tools for Damage Localisation by Decomposition of Lamb Wave Signals
Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden +2
Ultrasonic guided waves offer a convenient and practical approach to structural health monitoring and non-destructive evaluation, thanks to some distinct advantages. Guided waves,…
On statistic alignment for domain adaptation in structural health monitoring
Jack Poole, Paul Gardner, Nikolaos Dervilis +2
The practical application of structural health monitoring (SHM) is often limited by the availability of labelled data. Transfer learning - specifically in the form of domain adapta…
A Bayesian Approach for Shaft Centre Localisation in Journal Bearings
Christopher A. Lindley, Scott Beamish, Rob Dwyer-Joyce +2
It has been shown that ultrasonic techniques work well for online measuring of circumferential oil film thickness profile in journal bearings; unfortunately, they can be limited by…
On generative models as the basis for digital twins
G. Tsialiamanis, D. J. Wagg, N. Dervilis +1
A framework is proposed for generative models as a basis for digital twins or mirrors of structures. The proposal is based on the premise that deterministic models cannot account f…
On an application of graph neural networks in population based SHM
G. Tsialiamanis, C. Mylonas, E. Chatzi +3
Attempts have been made recently in the field of population-based structural health monitoring (PBSHM), to transfer knowledge between SHM models of different structures. The attemp…
On generating parametrised structural data using conditional generative adversarial networks
G. Tsialiamanis, D. J. Wagg, N. Dervilis +1
A powerful approach, and one of the most common ones in structural health monitoring (SHM), is to use data-driven models to make predictions and inferences about structures and the…
On the application of generative adversarial networks for nonlinear modal analysis
G. Tsialiamanis, M. D. Champneys, N. Dervilis +2
Linear modal analysis is a useful and effective tool for the design and analysis of structures. However, a comprehensive basis for nonlinear modal analysis remains to be developed.…
Modelling variability in vibration-based PBSHM via a generalised population form
Tina A Dardeno, Lawrence A Bull, Robin S Mills +2
Structural health monitoring (SHM) has been an active research area for the last three decades, and has accumulated a number of critical advances over that period, as can be seen i…
On robust risk-based active-learning algorithms for enhanced decision support
Aidan J. Hughes, Lawrence A. Bull, Paul Gardner +2
Classification models are a fundamental component of physical-asset management technologies such as structural health monitoring (SHM) systems and digital twins. Previous work intr…