Smart monitoring of aeronautical composites plates based on electromechanical impedance measurements and artificial neural networks

Pierre Selva 1 Olivier Cherrier 2 Valérie Pommier-Budinger 3, 2 Frederic Lachaud 2 Joseph Morlier 2
1 CT Ingénierie
2 ICA - Institut Clément Ader
3 DMIA - Département de Mathématiques, Informatique, Automatique
Abstract : This paper presents a structural health monitoring (SHM) method for in situ damage detection and localization in carbon fiber reinforced plates (CFRPs). The detection is achieved using the electromechanical impedance (EMI) technique employing piezoelectric transducers as high-frequency modal sensors. Numerical simulations based on the finite element method are carried out so as to simulate more than a hundred damage scenarios. Damage metrics are then used to quantify and detect changes between the electromechanical impedance spectrum of a pristine and damaged structure. The localization process relies on artificial neural networks (ANNs) whose inputs are derived from a principal component analysis of the damage metrics. It is shown that the resulting ANN can be used as a tool to predict the in-plane position of a single damage in a laminated composite plate.
Keywords : Artificial neural networks Structural health monitoring Composites Electromechanical impedance
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CNRS | INSA-TOULOUSE | ICA | INSA-GROUPE | UNIV-TLSE3

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Pierre Selva, Olivier Cherrier, Valérie Pommier-Budinger, Frederic Lachaud, Joseph Morlier. Smart monitoring of aeronautical composites plates based on electromechanical impedance measurements and artificial neural networks. Engineering Structures, Elsevier, 2013, 56, pp.794-804. ⟨10.1016/j.engstruct.2013.05.025⟩. ⟨hal-01851633⟩

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