Identifying Mode Shapes of Girder Bridges Using Dynamic Responses Extracted from a Moving Vehicle Under Impact Excitation

Author:

Qi Z. Q.1,Au F. T. K.1

Affiliation:

1. Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong

Abstract

The mode shapes of a bridge are important modal properties for many purposes, such as damage detection and model updating. Traditional methods for constructing mode shapes often require installation of instruments on the bridge for collection of dynamic responses. However, these methods are not only costly but also inconvenient. Therefore, a method is developed for constructing the mode shapes of girder bridges using the dynamic responses extracted from a moving vehicle under impact excitation. This paper reports some numerical simulations based on finite element modeling. First, the dynamic responses of a moving vehicle under impact excitation are generated for simulation. Then the component response associated with each natural frequency of the bridge is extracted by using a suitable filter. Finally, the mode shape associated with each natural frequency identified is constructed from the extracted component response and its Hilbert transform pair. The proposed method uses only the information measured from the moving vehicle, which acts both as a sensor and an exciter. Moreover, the additional impact excitation on the vehicle helps to excite the bridge. This helps to improve the accuracy by overcoming the adverse effects of measurement noise and road surface roughness. The effects of measurement noise, road surface roughness and vehicle speed on the accuracy of results are evaluated. A numerical study is presented to verify the feasibility of the proposed method.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Mechanical Engineering,Ocean Engineering,Aerospace Engineering,Building and Construction,Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3