• français
    • English
    English
  • Ouvrir une session
Aide
Voir le document 
  •   Accueil de SAM
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • Voir le document
  • Accueil de SAM
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • Voir le document
JavaScript is disabled for your browser. Some features of this site may not work without it.

Analytical modeling of vibrations in a damaged beam using Green-Volterra formalism

Communication avec acte
Auteur
BOUVIER, Damien
ccMECHBAL, Nazih
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ccRÉBILLAT, Marc

URI
http://hdl.handle.net/10985/19577
Date
2020

Résumé

Structural Health Monitoring of aeronautic composite structures through Lamb waves can advantageously exploit the fact that Lamb wave damage interaction is nonlinear. However, one di culty in this context is to be able to distinguish between nonlinearities due to the propagation (i.e. ma- terial or geometrical nonlinearities) and those due to the damage itself that are of main interest here. This work proposes to use the Green-Volterra formal- ism to build up a model for Lamb Wave propagation and damage interaction that is complex enough to represent both types of nonlinearities, and simple enough to be used for simulation and estimation purposes. This approach is presented for the low frequency S0 mode nonlinear propagation in a dam- aged beam. An analytical model of the nonlinear wave propagation is rst derived, where the damage is represented with a polynomial sti ness char- acteristic acting via boundary conditions. This model is then used to derive the Green-Volterra series describing the nonlinear input-output relationship of the system. A modal decomposition of the Green-Volterra series is also pro- vided. Simulations are presented, and the proposed approach is successfully compared to state-of-the-art methods based on nite-elements models.

Fichier(s) constituant cette publication

Nom:
PIMM_EWHSM_2020_BOUVIER.pdf
Taille:
2.565Mo
Format:
PDF
Description:
Communication avec actes
Voir/Ouvrir
CC BY-NC-ND
Ce document est diffusé sous licence CC BY-NC-ND

Cette publication figure dans le(s) laboratoire(s) suivant(s)

  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)

Documents liés

Visualiser des documents liés par titre, auteur, créateur et sujet.

  • A spatio-temporal nonlinear semi-analytical framework describing longitudinal waves propagation in damaged structures based on Green–Volterra formalism 
    Article dans une revue avec comité de lecture
    ccBOUVIER, Damien; ccRÉBILLAT, Marc; ccMONTEIRO, Eric; ccMECHBAL, Nazih (Elsevier, 2023-01)
    Structural 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 ...
  • Improving Lamb Wave detection for SHM using a dedicated LWDS electronics 
    Communication avec acte
    JAUSSAUD, Gladys; REBUFA, Jocelyn; FOURNIER, Marc; LOGEAIS, Matthieu; BENCHEIKH, Nabil; ccMECHBAL, Nazih; ccRÉBILLAT, Marc (NTD, 2019)
    In the context of Condition Based Maintenance (CBM) for aircrafts, Structural Health Monitoring (SHM) is one main field of research. Detection and localization of damages in a structure request reliability of the equipment ...
  • Laser shock a novel way to generate calibrated delamination in composites: concept and first results 
    Communication avec acte
    GHRIB, Meriem; BERTHE, Laurent; ECAULT, Romain; ccMECHBAL, Nazih; ccGUSKOV, Mikhail; ccRÉBILLAT, Marc (2015)
    Structural Health Monitoring (SHM) has been gaining importance in recent years. SHM aims at providing structures with similar functionality as the biological nervous system and it is organized into four main steps: detection, ...
  • A Probabilistic Multi-class Classifier for Structural Health Monitoring 
    Article dans une revue avec comité de lecture
    URIBE, Juan Sebastian; ccMECHBAL, Nazih; ccRÉBILLAT, Marc (Elsevier, 2015)
    In this paper, a probabilistic multi-class pattern recognition algorithm is developed for damage detection, localization, and quantification in smart mechanical structures. As these structures can face damages of different ...

Parcourir

Tout SAMLaboratoiresAuteursDates de publicationCampus/InstitutsCe LaboratoireAuteursDates de publicationCampus/Instituts

Lettre Diffuser la Science

Dernière lettreVoir plus

Statistiques de consultation

Publications les plus consultéesStatistiques par paysAuteurs les plus consultés

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales