4.5 Article

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

出版社

WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0219455415400246

关键词

Ambient vibration test; Bayesian modal identification; Bayesian model updating; Markov chain Monte Carlo simulation

资金

  1. Research Grants Council of the Hong Kong Special Administrative Region, China [9041758 (CityU 110012)]

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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.

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