In this paper, the identification problem is discussed for damping nonlinearity. In practical applications, nonlinear damping is widespread, which is inevitable in the vibration response. Within the wide range of nonlinear damping mechanisms, friction is surely one of the most common, and with a high impact on the dynamical behavior of structures. Two common kinds of friction are investigated: quadratic friction and Coulomb friction. Nonlinear damping parameters are identified by nonlinear subspace identification, where the damping nonlinearity of the system is considered as a feedback force applied to the underlying linear system and is identified utilizing the time domain data. Two simulation examples are conducted to verify the effectiveness of the method. Results confirm the effectiveness of the methodology in identifying damping nonlinearities.

Identification of Nonlinear Damping Using Nonlinear Subspace Method / Zhu, Rui; Marchesiello, Stefano; Anastasio, Dario; Jiang, Dong; Fei, Qingguo. - ELETTRONICO. - Advances in Nonlinear Dynamics - Proceedings of the Second International Nonlinear Dynamics Conference (NODYCON 2021), Volume 2:(2022), pp. 369-377. (Intervento presentato al convegno NODYCON 2021 - Second International Nonlinear Dynamics Conference tenutosi a Rome (Italy) nel 16-19 February 2021) [10.1007/978-3-030-81166-2_33].

Identification of Nonlinear Damping Using Nonlinear Subspace Method

Marchesiello, Stefano;Anastasio, Dario;
2022

Abstract

In this paper, the identification problem is discussed for damping nonlinearity. In practical applications, nonlinear damping is widespread, which is inevitable in the vibration response. Within the wide range of nonlinear damping mechanisms, friction is surely one of the most common, and with a high impact on the dynamical behavior of structures. Two common kinds of friction are investigated: quadratic friction and Coulomb friction. Nonlinear damping parameters are identified by nonlinear subspace identification, where the damping nonlinearity of the system is considered as a feedback force applied to the underlying linear system and is identified utilizing the time domain data. Two simulation examples are conducted to verify the effectiveness of the method. Results confirm the effectiveness of the methodology in identifying damping nonlinearities.
2022
978-3-030-81165-5
978-3-030-81166-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2957194