| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Mechbal, Nazih
Processes and Engineering in Mechanics and Materials
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (17/17 displayed)
- 2023Hybrid twin of RTM process at the scarce data limitcitations
- 2022Design and control of a new electrostrictive polymer based continuum actuator for endoscopic robotcitations
- 2022Design and control of a new electrostrictive polymer based continuum actuator for endoscopic robot ; JIMSScitations
- 2022Prediction of frequency and spatially dependent attenuation of guided waves propagating in mounted and unmounted A380 parts made up of anisotropic viscoelastic composite laminatescitations
- 2022Experimental Damage Localization and Quantification with a Numerically Trained Convolutional Neural Network
- 2020Extrapolation of AR models using cubic splines for damage progression evaluation in composite structurescitations
- 2019Data-Driven Autoregressive Model Identification for Structural Health Monitoring in an Anisotropic Composite Plate.
- 2019Data-Driven Autoregressive Model Identification for Structural Health Monitoring in an Anisotropic Composite Plate.
- 2019Piezoelectric transducer for low frequency sound generation on surface loudspeakers
- 2019Investigation of nonlinear Lamb wave/damage interaction: numerical and experimental approaches
- 2018Optimal dual-PZT sizing and network design for baseline-free SHM of complex anisotropic composite structurescitations
- 2018LASER shock delamination generation and machine learning-based damage quantification in CFRP composites plates
- 2017Generation of controlled delaminations in composites using symmetrical laser shock configurationcitations
- 2017Estimation of the temperature field on a composite fan cowl using the static capacity of surface-mounted piezoceramic transducers
- 2017Estimation of the temperature field on a composite fan cowl using the static capacity of surface-mounted piezoceramic transducerscitations
- 2015Perturbation Analysis for Robust Damage Detection with Application to Multifunctional Aircraft Structures
- 2010Active Damage Detection and Localization Applied to Composite Structure Using Piezoceramic Patches
Places of action
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document
Data-Driven Autoregressive Model Identification for Structural Health Monitoring in an Anisotropic Composite Plate.
Abstract
A simple data-driven AutoRegressive (AR) model may be used to assess a model to describe and to predict the time-series outputs of the PZT sensors receiving Lamb waves for different operating conditions in composite structures. Thus, this paper presents the potentiality of the use of a set of AR models to detect, locate, and, manly, to extrapolate a damage sensitive index based on changes in onestep- ahead prediction errors. To illustrate this proposal, an aeronautical composite panel with bonded piezoelectric elements, that act both as sensors and actuators, is used to study the relationship between the variation of the parameters of the identified model and the presence of various simulated damage. A damage progression evaluation by extrapolating the AR parameters is also suggested and examined based on cubic spline functions to verify the future state and to observe how the damage could evolute, based on some simplified assumptions. This step could help to make a decision about a possible required repair without adopting a complicated and costly physical model.