Parameter identification for stick–slip friction model and its application to dynamic analysis of mechanical system

Abstract

Stick-slip friction (SSF), as an interesting dynamic behavior, is widely presented in mechanical systems, and has a significant effect on the mechanical systems’ lifespan and operation accuracy. Accurate SSF models are crucial for the effective evaluation of the dynamic performance of mechanical systems. Therefore, this paper focuses on proposing the parameter identification method for SSF models to ensure their simulation accuracy. The typical spring-block model is used for this work, which can reflect the coupling relationship between friction force and systems’ deformation. The corresponding experimental system is established to measure the characteristic values of SSF. Then, the optimization calculation-based parameter identification is carried out. The key input parameters of the SSF model are defined as design variables, and the optimization objective is to minimize the error between experimental and simulation results. Especially, multiple working conditions are considered, and the surrogate models are introduced to improve the optimization efficiency. Finally, the SSF model is fed into dynamic models of the typical mechanical system, and the dynamic responses before and after parameter identification are comparatively analyzed. This work can provide theoretical guidance for the accurate dynamic modeling of mechanical systems.