Multiple stochastic Volterra models for damage detection

Luis Gustavo Giacon Villani (1) , Samuel da Silva (1) , Americo Cunha Jr (2) , Michael Douglas Todd (3)

1 UNESP - Universidade Estadual Paulista Júlio de Mesquita Filho = São Paulo State University
2 UERJ - Universidade do Estado do Rio de Janeiro [Brasil] = Rio de Janeiro State University [Brazil] = Université d'État de Rio de Janeiro [Brésil]
3 UC San Diego - University of California [San Diego]

An intrinsically nonlinear operation can complicate the damage detection process. Furthermore, the data variation related to actual measured signals makes the use of stochastic approaches essential, improving the reliability of the methods. Therefore, a stochastic version of the Volterra series based on the idea of multiple models (MM) is proposed to describe the behavior of the nonlinear structures in reference conditions, and statistical tools are implemented to introduce a hypothesis test to detect damage considering the presence of uncertainties.

Domaines: Vibrations [physics.class-ph]; Probabilités [math.PR]; Statistiques [math.ST]; Mécanique des structures [physics.class-ph]; Mécanique des solides [physics.class-ph]; Génie mécanique [physics.class-ph]

Luis Gustavo Giacon Villani, Samuel da Silva, Americo Cunha Jr, Michael Douglas Todd. Multiple stochastic Volterra models for damage detection. XIV Conferência Brasileira de Dinâmica, Controle e Aplicações (DINCON 2019), Nov 2019, São Carlos, Brazil. ⟨hal-02388477⟩