Gaussian Process NARX Model for Damage Detection in Composite Aircraft Structures

Autor(es)

da Silva, Samuel ; Villani, Luis G. G. ; Rebillat, Marc ; Mechbal, Nazih

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF NONDESTRUCTIVE EVALUATION, DIAGNOSTICS AND PROGNOSTICS OF ENGINEERING SYSTEMS; v. 5, n. 1, p. 8-pg., 2022-02-01.

Resumo

This article demonstrates the Gaussian process regression model's applicability combined with a nonlinear autoregressive exogenous (NARX) framework using experimental data measured with PZTs' patches bonded in a composite aeronautical structure for concerning a novel structural health monitoring (SHM) strategy. A stiffened carbon-epoxy plate regarding a healthy condition and simulated damage on the center of the bottom part of the stiffener is utilized. Comparing the performance in terms of simulation errors is made to observe if the identified models can represent and predict the waveform with confidence bounds considering the confounding effect produced by noise or possible temperature variations assuming a dataset preprocessed using principal component analysis. The results of the GP-NARX identified model have attested correct classification with a reduced number of false alarms, even with model uncertainties propagation regarding healthy and damaged conditions. (AU)

• Processo FAPESP: 17/15512-8 - Identificação de modelos de ondas guiadas para prognóstico de danos em estruturas de material compósito
• Beneficiário: Samuel da Silva
• Modalidade de apoio: Bolsas no Exterior - Pesquisa
• Processo FAPESP: 19/19684-3 - Detecção e quantificação de danos em estruturas com juntas parafusadas
• Beneficiário: Samuel da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 15/25676-2 - Detecção robusta de danos em sistemas não lineares incertos
• Beneficiário: Luis Gustavo Giacon Villani
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto