87 citations · 560 across the 49 of their papers we have counts for
8 papers · 1 filter
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…
Machine Learning Approach to Model Order Reduction of Nonlinear Systems via Autoencoder and LSTM Networks
Thomas Simpson, Nikolaos Dervilis, Eleni Chatzi
In analyzing and assessing the condition of dynamical systems, it is necessary to account for nonlinearity. Recent advances in computation have rendered previously computationally…
On risk-based active learning for structural health monitoring
A. J. Hughes, L. A. Bull, P. Gardner +3
A primary motivation for the development and implementation of structural health monitoring systems, is the prospect of gaining the ability to make informed decisions regarding the…
Foundations of Population-Based SHM, Part IV: The Geometry of Spaces of Structures and their Feature Spaces
George Tsialiamanis, Charilaos Mylonas, Eleni Chatzi +3
One of the requirements of the population-based approach to Structural Health Monitoring (SHM) proposed in the earlier papers in this sequence, is that structures be represented by…
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…
Damage detection in operational wind turbine blades using a new approach based on machine learning
Kartik Chandrasekhar, Nevena Stevanovic, Elizabeth J. Cross +2
The application of reliable structural health monitoring (SHM) technologies to operational wind turbine blades is a challenging task, due to the uncertain nature of the environment…
A probabilistic risk-based decision framework for structural health monitoring
Aidan J. Hughes, Robert J. Barthorpe, N. Dervilis +2
Obtaining the ability to make informed decisions regarding the operation and maintenance of structures, provides a major incentive for the implementation of structural health monit…
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…