An improved perturbation method for stochastic finite element model updating

X. G. Hua, Yiqing Ni, Z. Q. Chen, J. M. Ko

Research output: Journal article publicationJournal articleAcademic researchpeer-review

111 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1845-1864
Number of pages20
JournalInternational Journal for Numerical Methods in Engineering
Issue number13
Publication statusPublished - 26 Mar 2008


  • Damage detection
  • FE model updating
  • Modal variability
  • Perturbation method
  • Tikhonov regularization
  • Uncertainty propagation

ASJC Scopus subject areas

  • Numerical Analysis
  • Engineering(all)
  • Applied Mathematics

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