David Garcia Cava
Cited by
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Vibration-based delamination diagnosis and modelling for composite laminate plates
D Garcia, R Palazzetti, I Trendafilova, C Fiorini, A Zucchelli
Composite Structures 130, 155-162, 2015
A multivariate data analysis approach towards vibration analysis and vibration-based damage assessment:: Application for delamination detection in a composite beam
D Garcia, I Trendafilova
Journal of Sound and Vibration 333 (25), 7036-7050, 2014
A study on the vibration-based self-monitoring capabilities of nano-enriched composite laminated beam
D Garcia, I Trendafilova, JD Inman
Smart Materials and Structures 25 (2016), 045011, 2016
An experimental study on the data-driven structural health monitoring of large wind turbine blades using a single accelerometer and actuator
D Garcia, D Tcherniak
Mechanical systems and signal processing 127, 102-119, 2019
Dynamical system analysis of unstable flow phenomena in centrifugal blower
D Garcia, M Stickland, G Liśkiewicz
Open Engineering 5 (1), 2015
Damage assessment for wind turbine blades based on a multivariate statistical approach
D García, D Tcherniak, I Trendafilova
Journal of Physics: Conference Series 628 (1), 012086, 2015
Stable or not stable? Recognizing surge based on the pressure signal
D Garcia, G Liśkiewicz
Transactions of the Institute of Fluid-Flow Machinery, 2016
Singular spectrum analysis for identifying structural nonlinearity using free-decay responses: Application detection and diagnosis in composite laminates
D Garcia, I Trendafilova
26th International Conference on Noise and Vibration Engineering, 2014
Multivariate statistical analysis for damage and delamination in composite structures
D Garcia, I Trendafilova
11th International conference on vibration problems, 2013
Mitigation of environmental variabilities in damage detection: A comparative study of two semi-supervised approaches
A Movsessian, BA Qadri, D Tcherniak, DG Cava, MD Ulriksen
EURODYN 2020: XI International Conference on Structural Dynamics, 2020
Virtual prototyping of an actuator-based structural health monitoring system of wind turbine blades
D Garcia, D Tcherniak, K Branner
28th International Conference on Noise and Vibration Engineering, ISMA 2018 …, 2018
Vibration-based health monitoring approach for composite structures using multivariate statistical analysis
D Garcia, I Trendafilova, H Al-Bugharbee
EWSHM-7th European workshop on structural health monitoring, 2014
Adaptive Feature Selection for Enhancing Blade Damage Diagnosis on an Operational Wind Turbine
A Movsessian, D Garcia, D Tcherniak
Proceedings of the 13th International Conference on Damage Assessment of …, 2019
An artificial neural network methodology for damage detection: Demonstration on an operating wind turbine blade
A Movsessian, D Garcia Cava, D Tcherniak
Mechanical systems and signal processing 159, 107766, 2021
Understanding the Influence of Environmental and Operational Variability on Wind Turbine Blade Monitoring
C Roberts, DG Cava, LD Avendaño-Valencia
European Workshop on Structural Health Monitoring, 109-118, 2020
Flow instabilities detection in centrifugal blower using empirical mode decomposition
M Stajuda, G Liśkiewicz, G David
Global Power & Propulsion Society, Beijing 2019, 2019
Strain estimation using modal expansion approach via virtual sensing for structural asset management
C Roberts, S Isbister, C Murphy, C Nisbet, P Sweeney, D Garcia Cava, ...
1st International Conference on Structural Integrity for offshore energy …, 2018
Study of Singular Spectrum Analysis as a data-driven technique for damage diagnosis. Comparison between the time or frequency domain
D Garcia, I Trendafilova
International Conference on Engineering Vibration 2017 (ICoEV 2017) 148, 2018
An investigation in vibration modeling and vibration-based monitoring for composite laminates
R Palazzetti, D Garcia, I Trendafilova, C Fiorini, A Zucchelli
KU Leuven, 2014
Polynomial Chaos-Kriging metamodel for quantification of the debonding area in large wind turbine blades
B Pavlack, J Paixão, S Da Silva, A Cunha Jr, D García Cava
Structural Health Monitoring, 14759217211007956, 2021
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