Global Identification of Linear Parameter-varying Vibration Systems

doi:10.3901/JME.2022.23.114

Abstract

Abstract: There are numerous linear parameter-varying vibration systems in manufacturing systems, whose characteristics vary with specific parameters. At present, they are mainly identified through local identification approaches, which cannot balance the identification accuracy and efficiency. In order to identify linear parameter-varying vibration systems accurately and efficiently, a global identification approach is proposed. Excitation should be applied continuously to a linear parameter-varying vibration system whose scheduling variables varies continuously at the same time. The vibration differential equation of the system is discretized in time domain, then the coefficient functions of it are characterized by an over-complete dictionary functions library and solved via sparse regression. And then, the system model can be identified from the data of excitation-response signals and scheduling variables directly. Based on the modal parameters of an actual tool tip structure, the surrogate model of a linear parameter-varying vibration system is established for verification. The average error percentage of modal parameters from global identification in the single-scheduling variable case and the multi-scheduling variables case are both less than 2.7%, which has fully shown the effectiveness of the proposed approach. In addition, the good results in the simulation environment also indicate the feasibility of the global identification for linear parameter-varying vibration systems.

Key words: linear parameter-varying system, vibration system, system identification, global identification, sparse regression

CLC Number:

TH113

CAI Yu, LIU Xu, CHENG Yinghao. Global Identification of Linear Parameter-varying Vibration Systems[J]. Journal of Mechanical Engineering, 2022, 58(23): 114-122.

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