• 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.

Damage type classification based on structures nonlinear dynamical signature

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

URI
http://hdl.handle.net/10985/10036
Date
2015

Résumé

Structural damages result in nonlinear dynamical signatures that significantly help for their monitoring. A damage type classification approach is proposed here that is based on a parallel Hammerstein models representation of the structure estimated by means of the Exponential Sine Sweep Method. This estimation method has been here extended to take into account for input signal amplitude which was not the case before. On the basis of these estimated models, three amplitude dependent damage indexes are built: one that monitors the shift of the resonance frequency of the structure, another the ratio of nonlinear versus linear energy in the output signal, and a last one the ratio of the energy coming from odd nonlinearities to the energy coming from even nonlinearities in the output signal. The slopes of these amplitude-dependent DIs are then used as coordinates to place the damaged structure under study within a three-dimensional space. A single mass-spring-damper system is considered to illustrate the ability of this space to classify different types of damage. Four types of damage with different severities are simulated through different spring nonlinearities: bilinear stiffness, dead zone, saturation, and Coulomb friction. For all severities, the four types of damage are extremely well separated within the proposed three-dimensional space, thus highlighting its high potential for classification purposes.

Fichier(s) constituant cette publication

Nom:
PIMM-IFAC-BAKIR-2015.pdf
Taille:
648.5Ko
Format:
PDF
Description:
Article principal
Voir/Ouvrir

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.

  • 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 ...
  • A General Bayesian Framework for Ellipse-based and Hyperbola-based Damage Localisation in Anisotropic Composite Plates 
    Article dans une revue avec comité de lecture
    FENDZI, Claude; ccMECHBAL, Nazih; ccGUSKOV, Mikhail; ccRÉBILLAT, Marc (SAGE Publications, 2016)
    This paper focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account for uncertainties from experimental ...

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