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Ambient Vibration Test, Modal Identification and Structural Model Updating Following Bayesian Framework

Author(s):


Medium: journal article
Language(s): English
Published in: International Journal of Structural Stability and Dynamics, , n. 7, v. 15
Page(s): 1540024
DOI: 10.1142/s0219455415400246
Abstract:

Structural health monitoring (SHM) of civil engineering structures based on vibration data includes three main components: ambient vibration test, modal identification and model updating. This paper discussed these three components in detail and proposes a general framework of SHM for practical application. First, a fast Bayesian modal identification method based on Fast Fourier Transform (FFT) is introduced for efficiently extracting modal parameters together with the corresponding uncertainties from ambient vibration data. A recently developed Bayesian model updating method using Markov chain Monte Carlo simulation (MCMCS) is then discussed. To illustrate the performance of the proposed modal identification and model updating methods, a scale-down transmission tower is investigated. Ambient vibration test is conducted on the target structure to obtain modal parameters. By using the measured modal parameters, model updating is carried out. The MCMC-based Bayesian model updating method can efficiently evaluate the posterior marginal PDFs of the uncertain parameters without calculating high-dimension numerical integration, which provides posterior uncertainties for the target systems.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1142/s0219455415400246.
  • About this
    data sheet
  • Reference-ID
    10352608
  • Published on:
    14/08/2019
  • Last updated on:
    14/08/2019
 
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