Professor Nikolaos Dervilis
BSc, MSc, PhD
Department of Mechanical Engineering
Professor
n.dervilis@sheffield.ac.uk
+44 114 222 7816
+44 114 222 7816
Room D224, Central Wing, Sir Frederick Mappin Building
Full contact details
Professor Nikolaos Dervilis
Department of Mechanical Engineering
Room D224, Central Wing
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
Department of Mechanical Engineering
Room D224, Central Wing
Sir Frederick Mappin Building
Mappin Street
Sheffield
S1 3JD
- Profile
-
Nikolaos Dervilis is a Professor in the Department of Mechanical Engineering at the University of Sheffield and a member of the Dynamics Research Group (DRG). He studied physics in the National and Kapodistrian University of Athens. Later, he obtained his MSc in Sustainable and Renewable Energy Systems from the University of Edinburgh in the Department of Electronics and Electrical Engineering. He obtained his PhD from the University of Sheffield, Mechanical Engineering Department in the field of machine learning for Structural Health Monitoring (SHM). His expertise focuses on SHM, pattern recognition, data analysis and nonlinear dynamics. He is especially engaged with renewable energy research, particularly wind turbine farms.
- Research interests
-
Nikolaos’s current research interests include:
- Structural Health Monitoring (SHM): machine learning and pattern recognition techniques for data analysis, structural damage characterisation and non-destructive evaluation methods.
- Onshore and offshore wind farms, sustainable energy systems.
- Data analysis and information learning tools.
- Nonlinear dynamics and advanced signal processing.
- Publications
-
Journal articles
- On a meta-learning population-based approach to damage prognosis. Mechanical Systems and Signal Processing, 209, 111119-111119.
- A probabilistic approach for acoustic emission based monitoring techniques: With application to structural health monitoring. Mechanical Systems and Signal Processing, 208, 110958-110958.
- On the hierarchical Bayesian modelling of frequency response functions. Mechanical Systems and Signal Processing, 208, 111072-111072.
- Towards a population-informed approach to the definition of data-driven models for structural dynamics. Mechanical Systems and Signal Processing, 200, 110581-110581.
- Identification of piecewise-linear mechanical oscillators via Bayesian model selection and parameter estimation. Mechanical Systems and Signal Processing, 196, 110300-110300.
- A full-scale wind turbine blade monitoring campaign: detection of damage initiation and progression using medium-frequency active vibrations. Structural Health Monitoring.
- A time-evolving digital twin tool for engineering dynamics applications. Mechanical Systems and Signal Processing, 188, 109971-109971.
- Reduced order modeling of non-linear monopile dynamics via an AE-LSTM scheme. Frontiers in Energy Research, 11.
- A Bayesian method for material identification of composite plates via dispersion curves. Sensors, 23(1).
- On the dynamic properties of statistically-independent nonlinear normal modes. Mechanical Systems and Signal Processing, 181, 109510-109510.
- On robust risk-based active-learning algorithms for enhanced decision support. Mechanical Systems and Signal Processing, 181, 109502-109502.
- Modelling variability in vibration-based PBSHM via a generalised population form. Journal of Sound and Vibration, 538, 117227-117227.
- On Topological Data Analysis for Structural Dynamics: An Introduction to Persistent Homology. ASME Open Journal of Engineering, 1.
- A sampling-based approach for information-theoretic inspection management. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 478(2262).
- Informative bayesian tools for damage localisation by decomposition of Lamb wave signals. Journal of Sound and Vibration. View this article in WRRO
- On the application of kernelised Bayesian transfer learning to population-based structural health monitoring. Mechanical Systems and Signal Processing, 167(Part B).
- On the application of generative adversarial networks for nonlinear modal analysis. Mechanical Systems and Signal Processing, 166, 108473-108473.
- A population-based SHM methodology for heterogeneous structures : transferring damage localisation knowledge between different aircraft wings. Mechanical Systems and Signal Processing, 172. View this article in WRRO
- Impact of blade structural and aerodynamic uncertainties on wind turbine loads. Wind Energy.
- Error motion trajectory-driven diagnostics of kinematic and non-kinematic machine tool faults. Mechanical Systems and Signal Processing, 164. View this article in WRRO
- Predicting local material thickness from steady-state ultrasonic wavefield measurements using a convolutional neural network. Ultrasonics.
- Bayesian modelling of multivalued power curves from an operational wind farm. Mechanical Systems and Signal Processing.
- On generative models as the basis for digital twins. Data-Centric Engineering, 2.
- Foundations of population-based SHM, Part IV : the geometry of spaces of structures and their feature spaces. Mechanical Systems and Signal Processing, 157.
- Machine learning approach to model order reduction of nonlinear systems via autoencoder and LSTM networks. Journal of Engineering Mechanics, 147(10).
- Structured machine learning tools for modelling characteristics of guided waves. Mechanical Systems and Signal Processing, 156. View this article in WRRO
- On the transfer of damage detectors between structures: an experimental case study. Journal of Sound and Vibration, 501.
- Overcoming the problem of repair in structural health monitoring: Metric-informed transfer learning. Journal of Sound and Vibration, 116245-116245.
- Comparing approaches for multi-axis kinematic positioning in machine tools. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture, 095440542110196.
- A probabilistic risk-based decision framework for structural health monitoring. Mechanical Systems and Signal Processing, 150, 107339-107339.
- Probabilistic inference for structural health monitoring: new modes of learning from data. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(1). View this article in WRRO
- Foundations of population-based SHM, part III : heterogeneous populations – mapping and transfer. Mechanical Systems and Signal Processing, 149. View this article in WRRO
- Foundations of population-based SHM, part II : heterogeneous populations – graphs, networks, and communities. Mechanical Systems and Signal Processing, 148. View this article in WRRO
- Foundations of population-based SHM, Part I : homogeneous populations and forms. Mechanical Systems and Signal Processing, 148. View this article in WRRO
- Normalising Flows and Nonlinear Normal Modes. IFAC-PapersOnLine, 54(7), 655-660.
- Towards the probabilistic analysis of small bowel capsule endoscopy features to predict severity of duodenal histology in patients with villous atrophy. Journal of Medical Systems, 44(11).
- Machine learning at the interface of structural health monitoring and non-destructive evaluation. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2182), 20190581-20190581.
- Machining centre performance monitoring with calibrated artefact probing. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture.
- Towards semi-supervised and probabilistic classification in structural health monitoring. Mechanical Systems and Signal Processing, 140. View this article in WRRO
- Probabilistic modelling of wind turbine power curves with application of heteroscedastic Gaussian Process regression. Renewable Energy, 148, 1124-1136. View this article in WRRO
- Damage detection in operational wind turbine blades using a new approach based on machine learning. Renewable Energy.
- Probabilistic active learning : an online framework for structural health monitoring. Mechanical Systems and Signal Processing, 134. View this article in WRRO
- Book Review. Journal of Sound and Vibration, 458, 347-348.
- Model selection and parameter estimation of dynamical systems using a novel variant of approximate Bayesian computation. Mechanical Systems and Signal Processing, 122, 364-386. View this article in WRRO
- Outlier ensembles: A robust method for damage detection and unsupervised feature extraction from high-dimensional data. Journal of Sound and Vibration. View this article in WRRO
- A Bayesian non-parametric clustering approach for semi-supervised Structural Health Monitoring. Mechanical Systems and Signal Processing, 119, 100-119. View this article in WRRO
- Active learning for semi-supervised structural health monitoring. Journal of Sound and Vibration, 437, 373-388. View this article in WRRO
- On evolutionary system identification with applications to nonlinear benchmarks. Mechanical Systems and Signal Processing, 112, 194-232. View this article in WRRO
- Nonlinear modal analysis via non-parametric machine
learning tools.. Strain: an international journal for experimental mechanics. View this article in WRRO
- Model selection and parameter estimation in structural dynamics using approximate Bayesian computation. Mechanical Systems and Signal Processing, 99, 306-325. View this article in WRRO
- Performance monitoring of a wind turbine using extreme function theory. Renewable Energy, 113, 1490-1502. View this article in WRRO
- Automatic Kernel Selection for Gaussian Processes Regression with Approximate Bayesian Computation and Sequential Monte Carlo. Frontiers in Built Environment, 3. View this article in WRRO
- A new methodology for automating acoustic emission detection of metallic fatigue fractures in highly demanding aerospace environments: An overview. Progress in Aerospace Sciences, 90, 1-11. View this article in WRRO
- Robust methods for outlier detection and regression for SHM applications.. International Journal of Sustainable Materials and Structural Systems. View this article in WRRO
- A Non-linear Manifold Strategy for SHM Approaches. Strain, 51(4), 324-331. View this article in WRRO
- On robust regression analysis as a means of exploring environmental and operational conditions for SHM data. Journal of Sound and Vibration, 347, 279-296. View this article in WRRO
- A Performance Monitoring Approach for the Novel Lillgrund Offshore Wind Farm. IEEE Transactions on Industrial Electronics, 62(10), 6636-6644. View this article in WRRO
- Aspects of structural health and condition monitoring of offshore wind turbines. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 373(2035), 20140075-20140075. View this article in WRRO
- Robust methods of inclusive outlier analysis for structural health monitoring. JOURNAL OF SOUND AND VIBRATION, 333(20), 5181-5195.
- Envelope analysis using the Teager-Kaiser Energy operator for condition monitoring of a wind turbine bearing. Applied Mechanics and Materials, 564, 170-175.
- An SHM view of a CFD model of Lillgrund wind farm. Applied Mechanics and Materials, 564, 164-169.
- Damage detection in RAPTOR telescope systems using time-frequency analysis methods. Key Engineering Materials, 588, 43-53.
- Machine learning applications for a wind turbine blade under continuous fatigue loading. Key Engineering Materials, 588, 166-174.
- On damage diagnosis for a wind turbine blade using pattern recognition. JOURNAL OF SOUND AND VIBRATION, 333(6), 1833-1850.
- Advanced tools for damage detection in wind turbines. Key Engineering Materials, 569-570, 547-554.
- Comparative study of robust novelty detection techniques. Key Engineering Materials, 569-570, 1109-1115.
- Condition monitoring of a wind turbine gearbox using the empirical mode decomposition method and outlier analysis. Proceedings of the 6th European Workshop - Structural Health Monitoring 2012, EWSHM 2012, 2, 1316-1323.
- Feasibility study on a full‐scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium‐frequency active vibrations. Wind Energy.
- Using Non‐contact Measurement of Water Surface Dynamics to Estimate River Discharge. Water Resources Research.
- On statistic alignment for domain adaptation in structural health monitoring. Structural Health Monitoring, 147592172211104-147592172211104.
- Domain-adapted Gaussian mixture models for population-based structural health monitoring. Journal of Civil Structural Health Monitoring.
- A Bayesian Approach for Shaft Centre Localisation in Journal Bearings. Mechanical Systems and Signal Processing.
- Autonomous ultrasonic inspection using bayesian optimisation and robust outlier analysis. Mechanical Systems and Signal Processing, 145. View this article in WRRO
- A Brief Introduction to Recent Developments in Population-Based Structural Health Monitoring. Frontiers in Built Environment, 6.
- Equation discovery for nonlinear dynamical systems: a Bayesian viewpoint. Mechanical Systems and Signal Processing.
- On risk-based active learning for structural health monitoring.
Chapters
- The Astir Glider Wing Dataset for Population-Based SHM, Special Topics in Structural Dynamics & Experimental Techniques, Volume 5 (pp. 19-25). Springer Nature Switzerland
- Data-Centric Monitoring of Wind Farms, Data Driven Methods for Civil Structural Health Monitoring and Resilience (pp. 120-180). CRC Press
- A Meta-Learning Approach to Population-Based Modelling of Structures, Data Science in Engineering, Volume 10 (pp. 63-71). Springer Nature Switzerland
- Towards Physics-Based Metrics for Transfer Learning in Dynamics, Data Science in Engineering, Volume 10 (pp. 73-81). Springer Nature Switzerland
- On Quantifying Data Normalisation via Cointegration with Topological Methods, Data Science in Engineering, Volume 10 (pp. 43-52). Springer Nature Switzerland
- A Population Form via Hierarchical Bayesian Modelling of the FRF, Data Science in Engineering, Volume 10 (pp. 95-103). Springer Nature Switzerland
- Data-Centric Monitoring of Wind Farms: Combining Sources of Information, Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications (pp. 120-180).
- Better Together: Using Multi-Task Learning to Improve Feature Selection Within Structural Datasets, Data Science in Engineering, Volume 10 (pp. 53-61). Springer Nature Switzerland
- A Topological Analysis of Cointegrated Data: A Z24 Bridge Case Study, Lecture Notes in Civil Engineering (pp. 1095-1106). Springer International Publishing
- On Modelling Statistically Independent Nonlinear Normal Modes with Gaussian Process NARX Models, Nonlinear Structures & Systems, Volume 1 (pp. 135-147). Springer International Publishing
- Approximate Bayesian Inference for Piecewise-Linear Stiffness Systems, Nonlinear Structures & Systems, Volume 1 (pp. 165-175). Springer International Publishing
- On the Use of Cycle-Consistent Generative Adversarial Networks for Nonlinear Modal Analysis, Topics in Modal Analysis & Parameter Identification, Volume 8 (pp. 45-57). Springer International Publishing
- On the Use of Variational Autoencoders for Nonlinear Modal Analysis, Nonlinear Structures & Systems, Volume 1 (pp. 297-300). Springer International Publishing
- Multilayer Input Deep Learning Applied to Ultrasonic Wavefield Measurements, Data Science in Engineering, Volume 9 (pp. 143-156). Springer International Publishing
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 989-1061). Springer New York
- Partially Supervised Learning for Data-Driven Structural Health Monitoring, Structural Integrity (pp. 389-411). Springer International Publishing
- Population-Based Structural Health Monitoring, Structural Integrity (pp. 413-435). Springer International Publishing
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72). Springer New York
- On Topological Data Analysis for SHM: An Introduction to Persistent Homology, Data Science in Engineering, Volume 9 (pp. 169-184). Springer International Publishing
- On Generating Parametrised Structural Data Using Conditional Generative Adversarial Networks, Data Science in Engineering, Volume 9 (pp. 35-46). Springer International Publishing
- On an Application of Graph Neural Networks in Population-Based SHM, Data Science in Engineering, Volume 9 (pp. 47-63). Springer International Publishing
- Application of a U-Net Convolutional Neural Network to Ultrasonic Wavefield Measurements for Defect Characterization, Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6 (pp. 167-181). Springer International Publishing
- Transferring Damage Detectors Between Tailplane Experiments, Data Science in Engineering, Volume 9 (pp. 199-211).
- New Modes of Inference for Probabilistic SHM, Lecture Notes in Civil Engineering (pp. 415-426). Springer International Publishing
- On Partitioning of an SHM Problem and Parallels with Transfer Learning, Topics in Modal Analysis & Testing, Volume 8 (pp. 41-50). Springer International Publishing
- Towards Population-Based Structural Health Monitoring, Part IV: Heterogeneous Populations, Transfer and Mapping, Model Validation and Uncertainty Quantification, Volume 3 (pp. 187-199). Springer International Publishing
- Towards Population-Based Structural Health Monitoring, Part I: Homogeneous Populations and Forms, Model Validation and Uncertainty Quantification, Volume 3 (pp. 287-302). Springer International Publishing
- Kernelised Bayesian Transfer Learning for Population-Based Structural Health Monitoring, Model Validation and Uncertainty Quantification, Volume 3 (pp. 209-215). Springer International Publishing
- An Evolutionary Approach to Learning Neural Networks for Structural Health Monitoring, Model Validation and Uncertainty Quantification, Volume 3 (pp. 237-246). Springer International Publishing
- Structural Health Monitoring and Damage Identification, Handbook of Experimental Structural Dynamics (pp. 1-72).
- Investigating Engineering Data by Probabilistic Measures, Special Topics in Structural Dynamics & Experimental Techniques, Volume 5 (pp. 77-81). Springer International Publishing
Conference proceedings papers
- Towards Exact Statistically Independent Nonlinear Normal Modes via the FPK Equation (pp 81-91)
- ANOMALY DETECTION IN OFFSHORE WIND TURBINE STRUCTURES USING HIERARCHICAL BAYESIAN MODELLING. Proceedings of the 14th International Workshop on Structural Health Monitoring
- PHYSICS-INFORMED TRANSFER LEARNING IN PBSHM: A CASE STUDY ON EXPERIMENTAL HELICOPTER BLADES. Proceedings of the 14th International Workshop on Structural Health Monitoring
- A DECISION FRAMEWORK FOR SELECTING INFORMATION-TRANSFER STRATEGIES IN POPULATION-BASED SHM. Proceedings of the 14th International Workshop on Structural Health Monitoring
- SHARING INFORMATION BETWEEN MACHINE TOOLS TO IMPROVE SURFACE FINISH FORECASTING. Proceedings of the 14th International Workshop on Structural Health Monitoring
- ACOUSTIC EMISSION SOURCE LOCATION USING BAYESIAN OPTIMISATION FOR A COMPOSITE HELICOPTER BLADE. Proceedings of the 14th International Workshop on Structural Health Monitoring
- HIERARCHICAL BAYESIAN MODELLING OF A FAMILY OF FRFS. Proceedings of the 14th International Workshop on Structural Health Monitoring
- DIMENSIONALITY REDUCTION OF ACTIVE VIBRATION DATA FOR DETECTION AND MONITORING OF PROGRESSIVE DAMAGE IN WIND TURBINE BLADE. Proceedings of the 14th International Workshop on Structural Health Monitoring
- DETECTION, LOCALISATION, AND QUANTIFICATION OF BOLT LOOSENESS IN AN ALUMINIUM PLATE USING LAMB WAVE ANALYSIS. Proceedings of the 14th International Workshop on Structural Health Monitoring
- WHEN IS AN SHM PROBLEM A MULTI-TASK- LEARNING PROBLEM?. Proceedings of the 14th International Workshop on Structural Health Monitoring
- ON THE USE OF MODEL-BASED VERSUS DATA-BASED APPROACHES FOR VIRTUAL SENSING IN SHM. Proceedings of the 14th International Workshop on Structural Health Monitoring
- A Bayesian Approach to Lamb-Wave Dispersion Curve Material Identification in Composite Plates (pp 139-149)
- On the Application of Partial Domain Adaptation for PBSHM (pp 408-418)
- Semi-supervised risk-based active learning using inspection and maintenance information. Proceedings of ISMA 2022-International Conference on Noise and Vibration Engineering and USD 2022-International Conference on Uncertainty in Structural Dynamics
- On the Application of Variational Auto Encoders (VAE) for Damage Detection in Rolling Element Bearings. Proceedings of the Thirteenth International Workshop on Structural Health Monitoring, IWSHM 2021 (pp 388-397). Lancaster, PA,. USA, 15 March 2022 - 17 March 2022. View this article in WRRO
- ON AN APPLICATION OF GENERATIVE ADVERSARIAL NETWORKS ON REMAINING LIFETIME ESTIMATION. Proceedings of the 13th International Workshop on Structural Health Monitoring
- INVESTIGATING EXPERIMENTAL REPEATABILITY AND FEATURE CONSISTENCY IN VIBRATION-BASED SHM. Proceedings of the 13th International Workshop on Structural Health Monitoring
- INVESTIGATING THE EFFECTS OF AMBIENT TEMPERATURE ON FEATURE CONSISTENCY IN VIBRATION-BASED SHM. Proceedings of the 13th International Workshop on Structural Health Monitoring
- NONLINEAR REDUCED ORDER MODELLING OF SOIL STRUCTURE INTERACTION EFFECTS VIA LSTM AND AUTOENCODER NEURAL NETWORKS. Proceedings of the 13th International Workshop on Structural Health Monitoring
- ON A POPULATION-BASED STRUCTURAL HEALTH MONITORING FRAMEWORK: AN AEROSPACE CASE STUDY. Proceedings of the 13th International Workshop on Structural Health Monitoring
- ON THE APPLICATION OF TOPOLOGICAL DATA ANALYSIS: A Z24 BRIDGE CASE STUDY. Proceedings of the 13th International Workshop on Structural Health Monitoring
- ON NORMALISATION FOR DOMAIN ADAPTATION IN POPULATION-BASED STRUCTURAL HEALTH MONITORING. Proceedings of the 13th International Workshop on Structural Health Monitoring
- On Affine Symbolic Regression Trees for the Solution of Functional Problems (pp 95-108)
- On the Application of the Generating Series for Nonlinear Systems with Polynomial Stiffness (pp 135-149)
- An Initial Concept for an Error-Based Digital Twin Framework for Dynamics Applications. Conference Proceedings of the Society for Experimental Mechanics Series (pp 81-89)
- On the application of heterogeneous transfer learning to population-based structural health monitoring. Data Science in Engineering, Volume 9 : Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 (pp 87-98). Virtual conference, 8 February 2021 - 11 February 2021.
- Challenges for SHM from structural repairs : an outlier-informed domain adaptation approach. Data Science in Engineering, Volume 9 : Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 (pp 75-86). Virtual conference, 8 February 2021 - 11 February 2021.
- Decomposition of multi-mode signals using dispersion curves and Bayesian linear regression. Health Monitoring of Structural and Biological Systems XV, 22 March 2021 - 27 March 2021.
- On Domain-Adapted Gaussian Mixture Models for Population-Based Structural Health Monitoring. International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII, Vol. 2021-June (pp 663-670)
- Automated Feature Extraction for Damage Detection: A Pseudo-fault Framework for Population-based SHM. International Conference on Structural Health Monitoring of Intelligent Infrastructure: Transferring Research into Practice, SHMII, Vol. 2021-June (pp 655-661)
- On the use of nonlinear normal modes for nonlinear reduced order modelling. EURODYN 2020 - XI International Conference on Structural Dynamics, Proceedings, Vol. II (pp 3865-3877). Athens, Greece, 23 November 2020 - 26 November 2020.
- Towards population-based structural health monitoring, Part II : heterogeneous populations and structures as graphs. Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics 2020, Vol. 8 (pp 177-187). Houston, TX, USA, 10 February 2020 - 13 February 2020. View this article in WRRO
- Modelling of Guided Waves in a Composite Plate Through a Combination of Physical Knowledge and Regression Analysis (pp 109-114)
- Towards population-based structural health monitoring, Part III: Graphs, networks and communities. Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics View this article in WRRO
- Lamb wave mode separation using dispersion curves. Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics (pp 2891-2898)
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series (pp v)
- AN APPLICATION OF GENERATIVE ADVERSARIAL NETWORKS IN STRUCTURAL HEALTH MONITORING. XI International Conference on Structural Dynamics, 23 November 2020 - 26 November 2020.
- A NEAT APPROACH TO STRUCTURAL HEALTH MONITORING. XI International Conference on Structural Dynamics, 23 November 2020 - 26 November 2020.
- Uncertainty quantification framework for structural model of wind turbine blades. Proceedings of the International Conference on Structural Dynamic , EURODYN, Vol. 2 (pp 3911-3920)
- On the quantification of structural uncertainties of blades and their effect on wind turbine loads. Proceedings of ISMA 2020 - International Conference on Noise and Vibration Engineering and USD 2020 - International Conference on Uncertainty in Structural Dynamics (pp 3853-3862)
- A probabilistic framework for online structural health monitoring : active learning from machining data streams. Journal of Physics: Conference Series, Vol. 1264. Valpre, Lyon, France, 15 April 2019 - 17 April 2019. View this article in WRRO
- Efficient parameter identification and model selection in nonlinear dynamical systems via sparse Bayesian learning. Journal of Physics: Conference Series, Vol. 1264(1). Valpre, Lyon, France, 15 April 2019 - 17 April 2019. View this article in WRRO
- A nonlinear robust outlier detection approach for SHM. 8th IOMAC - International Operational Modal Analysis Conference, Proceedings (pp 107-114) View this article in WRRO
- An Efficient Likelihood-Free Bayesian Computation for Model Selection and Parameter Estimation Applied to Structural Dynamics (pp 141-151)
- Active Learning Approaches to Structural Health Monitoring (pp 157-159)
- Statistical analysis of damage indicators based on ultrasonic testing with embedded piezoelectric transducers. 9th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019 (pp 251-262)
- Machine Learning for Energy Load Forecasting. Journal of Physics: Conference Series, Vol. 1106(1), 2 July 2018 - 4 July 2018. View this article in WRRO
- Outlier ensembles: An alternative robust method for inclusive outlier analysis with structural health monitoring data. 9th European Workshop on Structural Health Monitoring, EWSHM 2018
- A semi-supervised bayesian non-parametric approach to damage detection. 9th European Workshop on Structural Health Monitoring, EWSHM 2018
- Fault diagnosis of wind turbine structures using decision tree learning algorithms with big data. Safety and Reliability - Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018 (pp 3053-3062)
- Outlier analysis under uncertainty: Applications to structural health monitoring. Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics (pp 4985-4999)
- On the use of pseudo-damage to represent damage to structures in population-based Structural Health Monitoring. Proceedings of ISMA 2018 - International Conference on Noise and Vibration Engineering and USD 2018 - International Conference on Uncertainty in Structural Dynamics (pp 3709-3722)
- ABC-NS: a new computational inference method applied to parameter estimation and model selection in structural dynamics. 23 Congrès Français de Mécanique, 1 September 2017. View this article in WRRO
- Is it worth changing pattern recognition methods for structural health monitoring?. Journal of Physics: Conference Series, Vol. 842 View this article in WRRO
- Aspects of computational intelligence in structural dynamics: Structural health monitoring. 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 27 November 2017 - 1 December 2017.
- Aspects of Computational Intelligence in Structural Dynamics: Structural Health Monitoring. 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp 1677-1683)
- Wind Turbine Health Monitoring: Current and Future Trends with an Active Learning Twist (pp 119-129)
- In-Process Monitoring of Automated Carbon Fibre Tape Layup Using Ultrasonic Guided Waves (pp 179-188)
- Preface. Conference Proceedings of the Society for Experimental Mechanics Series (pp v)
- Identification of nonlinear dynamical systems using approximate Bayesian computation based on a sequential Monte Carlo sampler. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 2551-2565) View this article in WRRO
- An exploratory study of the suitability of a wind turbine blade as a nonlinear demonstrator. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 4069-4080) View this article in WRRO
- On the usage of active learning for SHM. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 4033-4043) View this article in WRRO
- Exploring Environmental and Operational Variations in SHM Data Using Heteroscedastic Gaussian Processes (pp 145-153)
- Simplifying Transformations for Nonlinear Systems: Part II, Statistical Analysis of Harmonic Cancellation (pp 321-326) View this article in WRRO
- Simplifying Transformations for Nonlinear Systems: Part I, An Optimisation-Based Variant of Normal Form Analysis (pp 315-320) View this article in WRRO
- Experimental evaluation of environmental effects on a polymer-coated aluminium structure: A time-series analysis and pattern recognition approach. Proceedings of ISMA 2016 - International Conference on Noise and Vibration Engineering and USD2016 - International Conference on Uncertainty in Structural Dynamics (pp 3295-3307) View this article in WRRO
- Structural Health Monitoring: from Structures to Systems-of-Systems ★ ★The support of the UK Engineering and Physical Sciences Research Council (EPSRC) through grant reference numbers EP/J016942/1 and EP/K003836/2, and that of the EU Framework 7 Programme for the ITN project SYSWIND, is gratefully acknowledged.. IFAC-PapersOnLine, Vol. 48(21) (pp 1-17)
- Wind turbine structural health monitoring: A short investigation based on SCADA data. 7th European Workshop on Structural Health Monitoring, EWSHM 2014 - 2nd European Conference of the Prognostics and Health Management (PHM) Society (pp 512-519)
- Nonlinear modal analysis using pattern recognition. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 3017-3028) View this article in WRRO
- Nonlinear robust regression analysis as a means of exploring SHM data. Proceedings of ISMA 2014 - International Conference on Noise and Vibration Engineering and USD 2014 - International Conference on Uncertainty in Structural Dynamics (pp 513-525)
- Auto-Association and Novelty Detection: Truths and Myths?. STRUCTURAL HEALTH MONITORING 2013, VOLS 1 AND 2 (pp 243-250)
- Impact damage detection for composite material typical of wind turbine blades using novelty detection. Proceedings of the 6th European Workshop - Structural Health Monitoring 2012, EWSHM 2012, Vol. 2 (pp 1287-1296)
- Structural Health Monitoring of composite material typical of wind turbine blades by novelty detection on vibration response. Key Engineering Materials, Vol. 518 (pp 319-327)
- Novelty detection applied to vibration data from a CX-100 wind turbine blade under fatigue loading.. MODERN PRACTICE IN STRESS AND VIBRATION ANALYSIS 2012 (MPSVA 2012), Vol. 382
- Use of the Teager-Kaiser energy operator for condition monitoring of a wind turbine gearbox. PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2012) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2012) (pp 4255-4268)
- On damage detection in wind turbine gearboxes using outlier analysis. Proceedings of SPIE - The International Society for Optical Engineering, Vol. 8343
- Damage detection in carbon composite material typical of wind turbine blades using auto-associative neural networks. Proceedings of SPIE - The International Society for Optical Engineering, Vol. 8348
- Gaussian Processes for Structural Health Monitoring of Wind Turbine Blades. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018. View this article in WRRO
- Experimental Validation of the Population-Form to Represent Nominally-Identical Systems. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Structural Health Monitoring: A Review of Uncertainty Quantification Methods in Wind Turbine Systems. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Damage Classification Using Labelled and Unlabelled Measurements. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Applying the Concept of Complexity to Structural Health Monitoring. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Health Monitoring of Composite Structures by Combining Ultrasonic Wave Data. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Assessing the Likelihood of Damage at the Start of a Structural Health Monitoring Campaign. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Automated Fault Diagnosis with Calibrated Artefact Probing. Structural Health Monitoring 2019, 24 October 2018 - 26 October 2018.
- Towards a Population-based SHM: A Case Study on an Offshore Wind Farm. Structural Health Monitoring 2015
- Extreme Function Theory for SHM: A Case Study for Wind Turbines. Structural Health Monitoring 2015
- A Gaussian Process Form for Population-Based Structural Health Monitoring. DAMAS 2019 View this article in WRRO
- On the Structural Health Monitoring of Operational Wind Turbine Blades. Structural Health Monitoring 2017, 12 September 2017 - 14 September 2017. View this article in WRRO
- A risk-based active learning approach to inspection scheduling. Proceedings of the 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure View this article in WRRO
Presentations
Preprints
- Monitoring-Supported Value Generation for Managing Structures and Infrastructure Systems, arXiv.
- Quantifying the value of information transfer in population-based SHM, arXiv.
- Sharing Information Between Machine Tools to Improve Surface Finish Forecasting, arXiv.
- Towards a population-informed approach to the definition of data-driven models for structural dynamics, arXiv.
- A decision framework for selecting information-transfer strategies in population-based SHM, arXiv.
- On the hierarchical Bayesian modelling of frequency response functions.
- When is an SHM problem a Multi-Task-Learning problem?, arXiv.
- VpROM: A novel Variational AutoEncoder-boosted Reduced Order Model for the treatment of parametric dependencies in nonlinear systems, arXiv.
- Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets, arXiv.
- A Meta-Learning Approach to Population-Based Modelling of Structures.
- Towards a Population-Informed Approach to the Definition of Data-Driven Models for Structural Dynamics, Elsevier BV.
- On the application of the generating series for nonlinear systems with polynomial stiffness, arXiv.
- On topological data analysis for structural dynamics: an introduction to persistent homology, arXiv.
- On the application of topological data analysis: a Z24 Bridge case study.
- A topological analysis of cointegrated data: a Z24 Bridge case study, arXiv.
- A Bayesian Method for Material Identification of Composite Plates via Dispersion Curves, arXiv.
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