Techno Press
You logged in as Techno Press

Smart Structures and Systems
  Volume 27, Number 2, February 2021 , pages 257-266

Damage detection of bridge structures under unknown seismic excitations using support vector machine based on transmissibility function and wavelet packet energy
Lijun Liu, Jianan Mi, Yixiao Zhang and Ying Lei

    Since it may be hard to obtain the exact external load in practice, damage identification of bridge structures using only structural responses under unknown seismic excitations is an important but challenging task. Since structural responses are determined by both structural properties and seismic excitation, it is necessary to remove the effects of external excitation and only retain the structural information for structural damage identification. In this paper, a data-driven approach using structural responses only is proposed for structural damage alarming and localization of bridge structures. The transmissibility functions (TF) of structural responses are used to eliminate the influence of unknown seismic excitations. Moreover, the inverse Fourier transform of TFs and wavelet packet transform are used to reduce the influence of frequency bands and to extract the damagesensitive feature, respectively. Based on Support vector machines (SVM), structural responses under ambient excitations are used for training SVM. Then, structural responses under unknown seismic excitations are also processed accordingly and used for damage alarming and localization by the trained SMV. The numerical simulation examples of beam-type bridge and a cablestayed bridge under unknown seismic excitations are studied to illustrate the performance of the proposed approach.
Key Words
    structural damage identification; unknown seismic excitation; transmissibility function; wavelet packet energy; support vector machine
School of Architecture and Civil Engineering, Xiamen University, Xiamen 365001, China.

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2023 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: