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Nikolaos Dervilis
Nikolaos Dervilis
University of Sheffield, Dynamics Research Group, Sheffield, UK
Verified email at sheffield.ac.uk - Homepage
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Cited by
Cited by
Year
On damage diagnosis for a wind turbine blade using pattern recognition
N Dervilis, M Choi, SG Taylor, RJ Barthorpe, G Park, CR Farrar, K Worden
Journal of sound and vibration 333 (6), 1833-1850, 2014
1962014
On robust regression analysis as a means of exploring environmental and operational conditions for SHM data
N Dervilis, K Worden, EJ Cross
Journal of Sound and Vibration 347, 279-296, 2015
1672015
Foundations of population-based SHM, Part I: Homogeneous populations and forms
LA Bull, PA Gardner, J Gosliga, TJ Rogers, N Dervilis, EJ Cross, ...
Mechanical systems and signal processing 148, 107141, 2021
1472021
Foundations of population-based SHM, Part III: Heterogeneous populations–Mapping and transfer
P Gardner, LA Bull, J Gosliga, N Dervilis, K Worden
Mechanical Systems and Signal Processing 149, 107142, 2020
1442020
Fault diagnosis of wind turbine structures using decision tree learning algorithms with big data
I Abdallah, V Dertimanis, H Mylonas, K Tatsis, E Chatzi, N Dervili, ...
Safety and Reliability–Safe Societies in a Changing World, 3053-3061, 2018
1382018
Foundations of Population-based SHM, Part II: Heterogeneous populations–Graphs, networks, and communities
J Gosliga, PA Gardner, LA Bull, N Dervilis, K Worden
Mechanical Systems and Signal Processing 148, 107144, 2021
1282021
A new methodology for automating acoustic emission detection of metallic fatigue fractures in highly demanding aerospace environments: An overview
KM Holford, MJ Eaton, JJ Hensman, R Pullin, SL Evans, N Dervilis, ...
Progress in Aerospace Sciences 90, 1-11, 2017
1152017
Aspects of structural health and condition monitoring of offshore wind turbines
I Antoniadou, N Dervilis, E Papatheou, AE Maguire, K Worden
Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2015
1102015
A Bayesian non-parametric clustering approach for semi-supervised structural health monitoring
TJ Rogers, K Worden, R Fuentes, N Dervilis, UT Tygesen, EJ Cross
Mechanical Systems and Signal Processing 119, 100-119, 2019
932019
Model selection and parameter estimation in structural dynamics using approximate Bayesian computation
AB Abdessalem, N Dervilis, D Wagg, K Worden
Mechanical Systems and Signal Processing 99, 306-325, 2018
892018
A performance monitoring approach for the novel Lillgrund offshore wind farm
E Papatheou, N Dervilis, AE Maguire, I Antoniadou, K Worden
IEEE Transactions on Industrial Electronics 62 (10), 6636-6644, 2015
852015
Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian process regression
TJ Rogers, P Gardner, N Dervilis, K Worden, AE Maguire, E Papatheou, ...
Renewable Energy 148, 1124-1136, 2020
832020
Active learning for semi-supervised structural health monitoring
L Bull, K Worden, G Manson, N Dervilis
Journal of Sound and Vibration 437, 373-388, 2018
762018
Robust methods of inclusive outlier analysis for structural health monitoring
N Dervilis, EJ Cross, RJ Barthorpe, K Worden
Journal of Sound and Vibration 333 (20), 5181-5195, 2014
742014
Towards semi-supervised and probabilistic classification in structural health monitoring
LA Bull, K Worden, N Dervilis
Mechanical Systems and Signal Processing 140, 106653, 2020
722020
Probabilistic active learning: an online framework for structural health monitoring
LA Bull, TJ Rogers, C Wickramarachchi, EJ Cross, K Worden, N Dervilis
Mechanical Systems and Signal Processing 134, 106294, 2019
702019
Machine learning at the interface of structural health monitoring and non-destructive evaluation
P Gardner, R Fuentes, N Dervilis, C Mineo, SG Pierce, EJ Cross, ...
Philosophical Transactions of the Royal Society A 378 (2182), 20190581, 2020
672020
Automatic kernel selection for gaussian processes regression with approximate bayesian computation and sequential monte carlo
AB Abdessalem, N Dervilis, DJ Wagg, K Worden
Frontiers in Built Environment 3, 52, 2017
662017
On evolutionary system identification with applications to nonlinear benchmarks
K Worden, RJ Barthorpe, EJ Cross, N Dervilis, GR Holmes, G Manson, ...
Mechanical Systems and Signal Processing 112, 194-232, 2018
652018
Machine learning approach to model order reduction of nonlinear systems via autoencoder and LSTM networks
T Simpson, N Dervilis, E Chatzi
Journal of Engineering Mechanics 147 (10), 04021061, 2021
612021
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Articles 1–20