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Principal Least Squares Canonical Correlation Analysis for damage quantification in aeronautic composite structures

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

URI
http://hdl.handle.net/10985/19535
Date
2019

Résumé

The Structural Health Monitoring (SHM) process is classically decomposed into four steps: damage detection, localization, classification and quantification. Here the focus is put on aeronautic composite structures and specifically on the damage quantification step. For SHM purpose, such structures are equipped with piezoelectric elements that can be used both as sensors and actuators. To quantify a detected damage, measurements are first performed in a reference state. Then, during the life cycle of the structure several measurements at unknown states are performed. Several damage indexes are then extracted from the difference between the reference and unknown states. This damage indexes matrix is the basis of any algorithms dedicated to the quantification step but still contains many more dimensions that just a quantification of damage size. The question raised here is the efficiency of dimension reduction algorithms in the damage indexes space for quantification purposes. Performances of simple direct regression (SDR), principal component analysis (PCA), partial least squares (PLS), canonical correlation analysis (CCA) and autoencoders (AE) are investigated for this purpose. It is shown that PCA, PLS and CCA are all able to discover a low-dimensional space within the damage indexes space that is linearly related with the physical damage size, and that average prediction errors of the order of ≃ 1% can be achieved by projecting data through that low-dimensional space.

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Documents liés

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  • 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 ...

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