43 citations · 224 across the 18 of their papers we have counts for
18 papers
Latent variable models for simultaneous EOV identification and removal in population-based SHM
M. D. Champneys, M. R. Jones, A. J. Hughes +3
The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM). The difficulty is compounded…
Cost-informed dimensionality reduction for structural digital twin technologies
Aidan J. Hughes, Keith Worden, Nikolaos Dervilis +1
Classification models are a key component of structural digital twin technologies used for supporting asset management decision-making. An important consideration when developing c…
Active learning for regression in engineering populations: A risk-informed approach
Daniel R. Clarkson, Lawrence A. Bull, Chandula T. Wickramarachchi +5
Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applic…
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…
A spectrum of physics-informed Gaussian processes for regression in engineering
Elizabeth J Cross, Timothy J Rogers, Daniel J Pitchforth +2
Despite the growing availability of sensing and data in general, we remain unable to fully characterise many in-service engineering systems and structures from a purely data-driven…
A Robust Probabilistic Approach to Stochastic Subspace Identification
Brandon J. O'Connell, Timothy J. Rogers
Modal parameter estimation of operational structures is often a challenging task when confronted with unwanted distortions (outliers) in field measurements. Atypical observations p…
PAO: A general particle swarm algorithm with exact dynamics and closed-form transition densities
Max D. Champneys, Timothy J. Rogers
A great deal of research has been conducted in the consideration of meta-heuristic optimisation methods that are able to find global optima in settings that gradient based optimise…
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…
Physically Meaningful Uncertainty Quantification in Probabilistic Wind Turbine Power Curve Models as a Damage Sensitive Feature
J. H. Mclean, M. R. Jones, B. J. O'Connell +2
A wind turbines' power curve is easily accessible damage sensitive data, and as such is a key part of structural health monitoring in wind turbines. Power curve models can be const…
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…
Constraining Gaussian processes for physics-informed acoustic emission mapping
Matthew R Jones, Timothy J Rogers, Elizabeth J Cross
The automated localisation of damage in structures is a challenging but critical ingredient in the path towards predictive or condition-based maintenance of high value structures.…
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,…
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm
L. A. Bull, P. A. Gardner, T. J. Rogers +6
Power curves capture the relationship between wind speed and output power for a specific wind turbine. Accurate regression models of this function prove useful in monitoring, maint…
A Latent Restoring Force Approach to Nonlinear System Identification
Timothy J. Rogers, Tobias Friis
Identification of nonlinear dynamic systems remains a significant challenge across engineering. This work suggests an approach based on Bayesian filtering to extract and identify t…
Grey-box models for wave loading prediction
Daniel J Pitchforth, Timothy J Rogers, Ulf T Tygesen +1
The quantification of wave loading on offshore structures and components is a crucial element in the assessment of their useful remaining life. In many applications the well-known…
Probabilistic Inference for Structural Health Monitoring: New Modes of Learning from Data
Lawrence A. Bull, Paul Gardner, Timothy J. Rogers +3
In data-driven SHM, the signals recorded from systems in operation can be noisy and incomplete. Data corresponding to each of the operational, environmental, and damage states are…
Structured Machine Learning Tools for Modelling Characteristics of Guided Waves
Marcus Haywood-Alexander, Nikolaos Dervilis, Keith Worden +3
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 monit…
A Bayesian methodology for localising acoustic emission sources in complex structures
Matthew R. Jones, Tim J. Rogers, Keith Worden +1
In the field of structural health monitoring (SHM), the acquisition of acoustic emissions to localise damage sources has emerged as a popular approach. Despite recent advances, the…