Gaussian Process NARX Model for Damage Detection in Composite Aircraft Structures

Author(s)

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

• Document type: Journal article
• Source: JOURNAL OF NONDESTRUCTIVE EVALUATION, DIAGNOSTICS AND PROGNOSTICS OF ENGINEERING SYSTEMS; v. 5, n. 1, p. 8-pg., 2022-02-01.

Abstract

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)

• FAPESP's process: 17/15512-8 - Applications of model identification of guided wave propagation in composite structures for damage prognosis
• Grantee: Samuel da Silva
• Support Opportunities: Scholarships abroad - Research
• FAPESP's process: 19/19684-3 - Nonlinear structural health monitoring of structures assembled by bolted joints
• Grantee: Samuel da Silva
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/25676-2 - Robust damage detection in uncertain nonlinear systems
• Grantee: Luis Gustavo Giacon Villani
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)