Vehicle Response-Based Bridge Modal Identification Using Different Time–Frequency Analysis Methods

Author:

Kong Xuan1ORCID,Tang Quanyu1,Luo Kui1ORCID,Hu Jiexuan1,Li Jinzhao1,Cai C. S.23ORCID

Affiliation:

1. Key Laboratory for Damage Diagnosis of Engineering Structures of Hunan Province, College of Civil Engineering, Hunan University, Changsha 410082, P. R. China

2. Department of Bridge Engineering, School of Transportation, Southeast University, Nanjing 211189, P. R. China

3. Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA

Abstract

Modal identification of bridges based on the responses of moving vehicles, termed as the indirect method, has drawn much attention in recent years. This indirect method has been proven to be capable of identifying bridge frequencies and mode shapes in the feasibility research. However, in the presence of additional factors such as vehicle speed and road surface roughness, it is difficult to identify high-order frequencies and high-resolution mode shapes of the bridge. The authors previously proposed a tractor-double-trailers model and the time–domain subtraction method to obtain the relative displacement of two trailers for bridge modal identification. In this study, the authors develop a methodology to improve the identification performance by combining the EMD technique and the time–frequency analysis method. The EMD technique is applied to separate the multi-source response signals of the trailers to obtain the signal component that contains only the bridge vibration. Then, different time–frequency analysis methods such as the short-time Fourier transform (STFT), Wigner–Ville distribution (WVD), and continuous wavelet transform (CWT) are adopted to construct the high-resolution bridge mode shapes. Numerical studies with one-dimensional and three-dimensional bridge models are conducted to verify the proposed method and investigate the effects of different factors. Finally, a laboratory test is implemented on a scaled bridge to verify the performance of the proposed method. The results show that the proposed method is able to separate the vehicle frequency and bridge frequencies, which facilitates the identification of bridge frequencies from the dynamic response of moving vehicles. Meanwhile, the CWT method performs the best in the identification of modal shapes among the three time–frequency analysis methods.

Funder

National Natural Science Foundation of China

Science Foundation for Excellent Young Scholars of Hunan Province

Publisher

World Scientific Pub Co Pte Ltd

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