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
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
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
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
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
Singular spectrum analysis as a tool for early detection of centrifugal compressor flow instability
A Logan, D Garcia Cava, G Liśkiewicz
Measurement 173, 108536, 2021
Understanding the Influence of Environmental and Operational Variability on Wind Turbine Blade Monitoring
C Roberts, D Garcia Cava, LD Avendaño-Valencia
European Workshop on Structural Health Monitoring, 109-118, 2020
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
Virtual prototyping of an actuator-based structural health monitoring system of wind turbine blades
D Garcia Cava, D Tcherniak, K Branner
In Proceedings of 28th International Conference on Noise and Vibration …, 2018
Stable or not stable? Recognizing surge based on the pressure signal
D Garcia, G Liśkiewicz
Transactions of the Institute of Fluid-Flow Machinery, 2016
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
Multivariate statistical analysis for damage and delamination in composite structures
D Garcia, I Trendafilova
11th International conference on vibration problems, 2013
A semi-supervised interpretable machine learning framework for sensor fault detection
P Martakis, A Movsessian, Y Reuland, SGS Pai, S Quqa, DG Cava, ...
Smart Structures Syst An Int J 29, 251-266, 2021
Mitigation of environmental variabilities in damage detection: A comparative study of two semi-supervised approaches
A Movsessian, BA Qadri, D Tcherniak, D Garcia Cava, MD Ulriksen
EURODYN 2020: XI International Conference on Structural Dynamics, 2020
Flow instabilities detection in centrifugal blower using empirical mode decomposition
M Stajuda, G Liśkiewicz, D Garcia Cava
Global Power & Propulsion Society, Beijing 2019, 2019
A Comparative Study on Data Manipulation in PCA-Based Structural Health Monitoring Systems for Removing Environmental and Operational Variations
C Roberts, D Garcia, D Tcherniak
Proceedings of the 13th International Conference on Damage Assessment of …, 2019
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
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 Garcia Cava
Structural Health Monitoring 21 (2), 666-682, 2022
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