Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/11596
Title: An improved perturbation method for stochastic finite element model updating
Authors: Hua, XG
Ni, YQ 
Chen, ZQ
Ko, JM
Keywords: Damage detection
FE model updating
Modal variability
Perturbation method
Tikhonov regularization
Uncertainty propagation
Issue Date: 2008
Publisher: John Wiley & Sons Ltd
Source: International journal for numerical methods in engineering, 2008, v. 73, no. 13, p. 1845-1864 How to cite?
Journal: International Journal for Numerical Methods in Engineering 
Abstract: In this paper, an improved perturbation method is developed for the statistical identification of structural parameters by using the measured modal parameters with randomness. On the basis of the first-order perturbation method and sensitivity-based finite element (FE) model updating, two recursive systems of equations are derived for estimating the first two moments of random structural parameters from the statistics of the measured modal parameters. Regularization technique is introduced to alleviate the ill-conditioning in solving the equations. The numerical studies of stochastic FE model updating of a truss bridge are presented to verify the improved perturbation method under three different types of uncertainties, namely natural randomness, measurement noise, and the combination of the two. The results obtained using the perturbation method are in good agreement with, although less accurate than, those obtained using the Monte Carlo simulation (MCS) method. It is also revealed that neglecting the correlation of the measured modal parameters may result in an unreliable estimation of the covariance matrix of updating parameters. The statistically updated FE model enables structural design and analysis, damage detection, condition assessment, and evaluation in the framework of probability and statistics.
URI: http://hdl.handle.net/10397/11596
DOI: 10.1002/nme.2151
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