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A dynamic response prediction model of nonlinear hysteretic isolators based on quasi-static characteristics and dynamic compensations

  • Ningning Huangfu
  • , Ying Zhang
  • , Yaguo Lei
  • , Qinghua Liu
  • , Wei Hsin Liao
  • , Zhenyang Zhao
  • , Junyi Cao
  • Xi'an Jiaotong University
  • Nanjing Forestry University
  • Chinese University of Hong Kong

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Nonlinear hysteretic isolators are widely applied in the field of vibration isolation due to their excellent energy dissipation capacity. However, the dynamic response prediction of nonlinear hysteretic isolators highly depends on accurate modeling methods for nonlinear hysteresis under varying conditions. This paper proposes a dynamic response prediction model based on quasi-static characteristics to precisely characterize the dynamic properties of nonlinear hysteretic isolators. The model employs a normalized Bouc-Wen framework, extended by polynomials, to describe the possible nonlinear stiffness and asymmetric hysteretic behaviors under quasi-static loading conditions. Additionally, global nonlinear elastic and damping terms are introduced to further capture the dynamic hysteretic characteristics over a wider range of operating velocities. The model parameters can be identified through quasi-static cyclic loading experiments and dynamic sinusoidal experiments. Then, the parametric model representing the restoring force is integrated into the dynamic equation for dynamic response prediction of the isolation object. The effectiveness of the proposed model is experimentally validated using an assembled hysteretic isolator. With limited testing data at specific amplitudes and frequencies, the resonance frequencies under steady-state excitations and the root mean square values under stochastic excitations are predicted with average accuracies of 97.40% and 97.09%, respectively.

Original languageEnglish
Article number112170
JournalMechanical Systems and Signal Processing
Volume224
DOIs
StatePublished - 1 Feb 2025

Keywords

  • Dynamic response prediction
  • Hysteresis model
  • Nonlinear isolators
  • Parameter identification

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