Modal parameters identification of bridge by improved stochastic subspace identification method with Grubbs criterion

Yulin Zhou,Xin Li,Hao Sun,Mingjin Zhang,Jinxiang Zhang,Xulei Jiang

doi:10.1177/0020294021993831

Abstract

In the wind tunnel test of a long-span bridge model, to ensure that the dynamic characteristics of the model can satisfy the test design requirements, it is particularly important to accurately identify the modal parameters of the model. First, the stochastic subspace identification algorithm was used to analyze the modal parameters of the model in the wind tunnel test; then, Grubbs criterion was introduced to effectively eliminate outliers in the damping ratio matrix. Stochastic subspace identification algorithm with Grubbs criterion improved the accuracy of the modal parameter identification and the ability to determine system matrix order and prevented the modal omissions caused by determining the stable condition of the damping ratio in the stability diagram. Finally, Oujiang Bridge was used as an example to verify the stochastic subspace identification algorithm with Grubbs criterion and compare with the results of the finite element method. The example shows that the improved method can be effectively applied to the modal parameter identification of bridges.

Highlights

Modal parameters are key parameters for the design and establishment of aeroelastic models
This paper introduces Grubbs criterion to detect outliers to effectively eliminate outliers in the damping ratio matrix and improve the ability of the stability graph to determine the order of the system
The specific conclusions are as follows: 1. The stability diagram method can effectively determine the order of the system, and proper adjustment of the parameters in Grubbs criterion can eliminate false modes and avoid modal omissions

Summary

Introduction

Modal parameters are key parameters for the design and establishment of aeroelastic models. When stability diagram method is applied to stochastic subspace identification algorithm, the modal omission might be caused due to larger damping ratio dispersion. Stochastic subspace identification algorithm with Grubbs criterion is introduced to optimize the process of determining the damping ratio stability.

Results

Conclusion