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Nonlinear feature extraction in a mechanical system using kernel PCA and output-only data: Experiment and physical insights

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Autor(es):
Nogueira, Wellington de Lima ; Scussel, Oscar ; Figueiredo, Eloi ; da Silva, Samuel
Número total de Autores: 4
Tipo de documento: Artigo Científico
Fonte: MECHANICAL SYSTEMS AND SIGNAL PROCESSING; v. 242, p. 23-pg., 2025-11-14.
Resumo

Identifying features in nonlinear structures, especially when they already exhibit inherent nonlinear behavior in the undamaged conditions, remains a significant challenge in structural health monitoring (SHM), particularly when the damage mechanism is also nonlinear. This complexity further increases in field applications, where controlling and measuring excitation is particularly challenging. Traditional methods, which rely on frequency response functions (FRFs), are unsuitable for nonlinear structures because they require knowledge of the excitation source and cannot effectively separate inherent nonlinearities from structural changes. This paper presents an output-only approach that combines transmissibility functions and kernel principal component analysis (KPCA) for damage detection in structures with nonlinear behavior caused by cubic stiffness and breathing crack effects. A numerical validation on a nonlinear multi-degree-of-freedom (MDOF) system with multiple resonances, followed by an experimental application on a nonlinear flexible beam, was performed to demonstrate the method's generalization and practical relevance. The experimental beam exhibits cubic nonlinearity in the undamaged condition, while the simulated damage, a breathing crack, introduced additional quadratic stiffness effects. KPCA successfully separated cubic and quadratic nonlinear effects by analyzing transmissibility functions between accelerometer pairs, enabling accurate damage detection. This framework addresses the limitations of FRF-based methods, providing a straightforward and valuable tool for practical applications in SHM that does not rely on complex machine learning techniques. (AU)

Processo FAPESP: 24/00720-8 - Desenvolvimento de Métricas de Similaridade na Transferência de Aprendizado para Monitoramento da Integridade Estrutural
Beneficiário:Samuel da Silva
Modalidade de apoio: Auxílio à Pesquisa - Pesquisador Visitante - Internacional
Processo FAPESP: 24/13559-0 - INOVAZAS - INOvações na detecção de VAZamentos em tubulações de água usando dados de vibrAção de Superfície
Beneficiário:Oscar Scussel
Modalidade de apoio: Auxílio à Pesquisa - Regular