87 citations · 379 across the 17 of their papers we have counts for
6 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…
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…
Canonical-Correlation-Based Fast Feature Selection for Structural Health Monitoring
Sikai Zhang, Tingna Wang, Keith Worden +2
Feature selection refers to the process of selecting useful features for machine learning tasks, and it is also a key step for structural health monitoring (SHM). This paper propos…
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…
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…