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Gaussian process models for mitigation of operational variability in the structural health monitoring of wind turbines

Mechanical systems and signal processing, 2020-08, Vol.142, p.106686, Article 106686

2020

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Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression

Renewable energy, 2021-06, Vol.170, p.539-561

2021

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Effect of wind and wave properties in modal parameter estimates of an idling offshore wind turbine from long-term monitoring data

Mechanical systems and signal processing, 2023-03, Vol.187, p.109934, Article 109934

2023

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Robust mitigation of EOVs using multivariate nonlinear regression within a vibration-based SHM methodology

Mechanical systems and signal processing, 2024-02, Vol.208, p.111028, Article 111028

2024

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Damage/fault diagnosis in an operating wind turbine under uncertainty via a vibration response Gaussian mixture random coefficient model based framework

Mechanical systems and signal processing, 2017-07, Vol.91, p.326-353

2017

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Gaussian Mixture Random Coefficient model based framework for SHM in structures with time–dependent dynamics under uncertainty

Mechanical systems and signal processing, 2017-12, Vol.97, p.59-83

2017

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State space model-based harmonic decomposition of pseudo-periodic non-stationary multivariate signals

Signal processing, 2023-12, Vol.213, p.109192, Article 109192

2023

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Invisible Color Variations of Facial Erythema: A Novel Early Marker for Diabetic Complications?

Journal of diabetes research, 2019, Vol.2019, p.4583895-7

2019

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Feedback on the Surveillance 8 challenge: Vibration-based diagnosis of a Safran aircraft engine

Mechanical systems and signal processing, 2017-12, Vol.97, p.112-144

2017

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Multivariate GP-VAR models for robust structural identification under operational variability

Probabilistic engineering mechanics, 2020-04, Vol.60, p.103035, Article 103035

2020

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Video-based eye tracking performance for computer-assisted diagnostic support of diabetic neuropathy

Artificial intelligence in medicine, 2021-04, Vol.114, p.102050-102050, Article 102050

2021

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Diagonal time dependent state space models for modal decomposition of non-stationary signals

Signal processing, 2018-06, Vol.147, p.208-223

2018

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Data-driven condition monitoring of two-stroke marine diesel engine piston rings with machine learning

Ships and offshore structures, 2023-08, p.1-13

2023

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Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability

Structure and infrastructure engineering, 2020-01, Vol.16 (1), p.138-168

2020

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Sensitivity driven robust vibration-based damage diagnosis under uncertainty through hierarchical Bayes time-series representations

Procedia engineering, 2017, Vol.199, p.1852-1857

2017

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Gaussian Process Time-Series Models for Structures under Operational Variability

Frontiers in built environment, 2017-12, Vol.3

2017

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Modelling long-term vibration monitoring data with Gaussian Process time-series models

IFAC-PapersOnLine, 2019, Vol.52 (28), p.26-31

2019

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Reducción de interferencia de línea de potencia en señales electrocardiográficas mediante el filtro dual de Kalman

Ingeniería e investigación, 2007-12, Vol.27 (3), p.77-88

2007

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State-space modal representations for decomposition of multivariate non-stationary signals

IFAC-PapersOnLine, 2021, Vol.54 (7), p.475-480

2021

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Axle Box Accelerometer Signal Identification and Modelling

Model Validation and Uncertainty Quantification, Volume 3, 2020, p.87-92

Mao, Zhu

2020

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Selección de características 2D en representaciones tiempo frecuencia para la detección de soplos cardíacos

Tecno - Lógicas (Instituto Tecnológico Metropolitano), 2011-06, Vol.26 (26), p.47-70

2011

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Metodología para evaluar el difeomorfismo de un atractor caótico usando el filtro de Kalman en señales fisiológicas

Tecno - Lógicas (Instituto Tecnológico Metropolitano), 2008-12, Vol.21 (21), p.31-48

2008

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Modelling long-term vibration monitoring data with Gaussian Process time-series models⁎⁎Prof. E.N. Chatzi gratefully acknowledges the support of the ERC Starting Grant WINDMIL (ERC-2015-StG 679843) on “Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines”

IFAC-PapersOnLine, 2019, Vol.52 (28), p.26-31

2019

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Estimación mejorada de modelos AR multivariados en el análisis de señales EEG

Revista de ingeniería, 2013-01, Vol.38 (38), p.20-26

2013

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Understanding the Influence of Environmental and Operational Variability on Wind Turbine Blade Monitoring

European Workshop on Structural Health Monitoring, p.109-118

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Environmental And Operational Variations
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Gaussian process models for mitigation of operational variability in the structural health monitoring of wind turbines

Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression

Effect of wind and wave properties in modal parameter estimates of an idling offshore wind turbine from long-term monitoring data

Robust mitigation of EOVs using multivariate nonlinear regression within a vibration-based SHM methodology

Damage/fault diagnosis in an operating wind turbine under uncertainty via a vibration response Gaussian mixture random coefficient model based framework

Gaussian Mixture Random Coefficient model based framework for SHM in structures with time–dependent dynamics under uncertainty

State space model-based harmonic decomposition of pseudo-periodic non-stationary multivariate signals

Invisible Color Variations of Facial Erythema: A Novel Early Marker for Diabetic Complications?

Feedback on the Surveillance 8 challenge: Vibration-based diagnosis of a Safran aircraft engine

Multivariate GP-VAR models for robust structural identification under operational variability

Video-based eye tracking performance for computer-assisted diagnostic support of diabetic neuropathy

Diagonal time dependent state space models for modal decomposition of non-stationary signals

Data-driven condition monitoring of two-stroke marine diesel engine piston rings with machine learning

Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability

Sensitivity driven robust vibration-based damage diagnosis under uncertainty through hierarchical Bayes time-series representations

Gaussian Process Time-Series Models for Structures under Operational Variability

Modelling long-term vibration monitoring data with Gaussian Process time-series models

Reducción de interferencia de línea de potencia en señales electrocardiográficas mediante el filtro dual de Kalman

State-space modal representations for decomposition of multivariate non-stationary signals

Axle Box Accelerometer Signal Identification and Modelling

Selección de características 2D en representaciones tiempo frecuencia para la detección de soplos cardíacos

Metodología para evaluar el difeomorfismo de un atractor caótico usando el filtro de Kalman en señales fisiológicas

Modelling long-term vibration monitoring data with Gaussian Process time-series models⁎⁎Prof. E.N. Chatzi gratefully acknowledges the support of the ERC Starting Grant WINDMIL (ERC-2015-StG 679843) on “Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines”

Estimación mejorada de modelos AR multivariados en el análisis de señales EEG

Understanding the Influence of Environmental and Operational Variability on Wind Turbine Blade Monitoring

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