Abstract

Ambient vibration analysis of a 18-story reinforced concrete building was carried out to investigate its dynamic properties. Ambient vibration test was conducted on the building, and modal parameters including natural frequencies and damping ratios were identified using the Frequency domain decomposition (FDD) method and the Enhanced frequency domain decomposition (EFDD) method. The results demonstrate that ambient vibration test is a feasible and efficient technique to excite structures, and that FDD and EFDD methods are reliable and efficient techniques for ambient vibration data.

Highlights

  • Ambient vibration test is a key technology in estimating dynamic properties of civil engineering structures

  • This paper investigates the dynamic properties of a newly designed and constructed 18-story reinforced concrete building by ambient modal analysis

  • In this paper ambient vibration test was conducted on a 18-story reinforced concrete building, and dynamic properties including natural frequencies and damping ratios were identified by the Frequency domain decomposition (FDD) and Enhanced frequency domain decomposition (EFDD) method

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Summary

Introduction

Ambient vibration test is a key technology in estimating dynamic properties of civil engineering structures. Ambient vibration test requires almost no equipment to excite structures, and no damage will be caused during test procedures, it is available for almost all kinds of civil engineering structures. This paper investigates the dynamic properties of a newly designed and constructed 18-story reinforced concrete building by ambient modal analysis. Ambient vibration test was conducted, and Frequency domain decomposition (FDD) method and Enhanced frequency domain decomposition (EFDD) method were employed to evaluate modal parameters. The purpose of this paper is to assess the feasibility of ambient vibration test technique for civil engineering structures and to evaluate the reliability and efficiency of FDD and EFDD methods for ambient vibration data

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