87 citations · 131 across the 4 of their papers we have counts for
4 papers
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…
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…