Experimental Damage Localization and Quantification with a Numerically Trained Convolutional Neural Network
Communication avec acte
Résumé
Structural Health Monitoring (SHM) based on Lamb wave propagation is a promising technology to optimize maintenance costs, enlarge service life and improve safety of aircrafts. A large quantity of data is collected during all the life cycle of the structure under monitoring and must be analysed in real time. We propose here to use 1D-CNN to estimate the severity and the localisation of a damage with the signals measured on a composite structure monitored with piezoelectric transducers (PZT). Two architectures have been tested: one takes for input the difference of the time signals of two different states and the second takes for in-puts temporal damage indexes. Those simple networks with a few layers predict with high precision the position and the severity of a damage in a composite plate. The evaluations on different cases show the robustness to simulated manufacturing uncertainties and noise. An evaluation on experimental measurement shows promising results to localise a damage on a real plate with a CNN trained with numerical data.
Fichier(s) constituant cette publication
- Nom:
- PIMM_EWSHM2022_2022_REBILLAT.pdf
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- 412.4Ko
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- Description:
- Experimental damage localization ...
- Fin d'embargo:
- 2022-12-22
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Documents liés
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Communication avec acteNumerical simulations of Structural Health Monitoring processes based on wave propagation can be very costly in terms of computation time, especially for complex aeronautic composite structures, and therefore strongly ...
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Communication sans acteThe deployment of Deep Learning (DL) strategies is particularly advantageous in Structural Health Monitoring (SHM) based of lamb Wave (LW) propagation due to the high quantity of data collected by the network of piezoelectric ...
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Article dans une revue avec comité de lecturePOSTORINO, Hadrien; MECHBAL, Nazih; MONTEIRO, Eric; RÉBILLAT, Marc (University of Liege library ( Belgium), 2023-04)In Lamb Waves based Structural Health Monitoring (LWSHM) of composite aeronautic structures, Deep Learning (DL) methods have proven to be promising to monitor damage using the signals collected by piezoelectric sensors ...
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Article dans une revue avec comité de lectureStructural Health Monitoring (SHM) of aeronautic structures by means of Lamb waves opens promising perspectives in terms of maintenance costs reduction and safety increases. Lamb waves interactions with damages are known ...