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

被引:47
|
作者
Yang, J. [1 ]
Lam, H. F. [1 ]
Hu, J. [1 ]
机构
[1] City Univ Hong Kong, Dept Architecture & Civil Engn, Hong Kong, Hong Kong, Peoples R China
关键词
Ambient vibration test; Bayesian modal identification; Bayesian model updating; Markov chain Monte Carlo simulation; FFT METHOD; UNCERTAINTIES; SYSTEM;
D O I
10.1142/S0219455415400246
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:16
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