| Title: |
Decision trees-based methods for the identification of damages in strongly damped plates for aerospace applications |
| Authors: |
Casaburo, Alessandro; Zwick, Cyril; Fossat, Pascal; Ardabilian, Mohsen; Bareille, Olivier; Sosson, Franck |
| Contributors: |
Laboratoire de Tribologie et Dynamique des Systèmes (LTDS); École Centrale de Lyon (ECL); Université de Lyon-Université de Lyon-École Nationale des Travaux Publics de l'État (ENTPE)-Ecole Nationale d'Ingénieurs de Saint Etienne (ENISE)-Centre National de la Recherche Scientifique (CNRS); Extraction de Caractéristiques et Identification (imagine); Pôle informatique graphique et géométrie (IGG); Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS); Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL); Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS); Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS); SMAC MontBlanc Technologies (SMAC) |
| Source: |
Italian Association of Aeronautics and Astronautics (A.I.D.A.A.) XXVII International Congress ; https://hal.science/hal-04928566 ; Italian Association of Aeronautics and Astronautics (A.I.D.A.A.) XXVII International Congress, Sep 2023, Padova, Italy. pp.146-149, ⟨10.21741/9781644902813-32⟩ |
| Publisher Information: |
CCSD |
| Publication Year: |
2023 |
| Collection: |
Portail HAL de l'Université Lumière Lyon 2 |
| Subject Terms: |
Machine Learning; Damage Identification; Vibration Test; Composite Plate; Composite Plate Vibration Test Damage Identification Machine Learning; [PHYS.MECA.VIBR]Physics [physics]/Mechanics [physics]/Vibrations [physics.class-ph]; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML] |
| Subject Geographic: |
Italy |
| Time: |
Padova, Italy |
| Description: |
International audience ; Abstract. Damage identification and localization is fundamental in industrial engineering, since it helps perform corrective actions in time to reduce as much as possible system downtime, operational costs, perform quick maintenance and avoid failure. Recently, structural health monitoring has found in machine learning an extremely useful tool, making the monitoring of complex systems more manageable. In this work, composite plates manufactured with the purpose of damping vibrations in aerospace structures are experimentally tested; the strong damping suddenly reduces the vibrations, leading to responses very similar to one another, without noticeable or structured differences between undamaged and damaged plates. To overcome this issue, machine learning methods are applied. Decision trees-based methods are chosen since they provide a combination of feature selection capabilities and robust classification performances. The used methods are decision trees themselves and two boosting methods: AdaBoost and RUSBoost. All three methods perform well in identifying damaged plates, the type (thickness damage and debonding) and sub-type of damage (thickness/debonding of types A and B). |
| Document Type: |
conference object |
| Language: |
English |
| DOI: |
10.21741/9781644902813-32 |
| Availability: |
https://hal.science/hal-04928566; https://doi.org/10.21741/9781644902813-32 |
| Accession Number: |
edsbas.FBBD44CA |
| Database: |
BASE |