Substructural time-varying parameter identification using wavelet multiresolution approximation

Yuanfeng Shi*, C. C. Chang

*Corresponding author for this work

Research output: Contribution to journalJournal Articlepeer-review

15 Citations (Scopus)

Abstract

Identifying properties of civil engineering structures is an important task for their condition assessment, damage diagnosis, maintenance and repair, and life-cycle management. These structures usually contain a large number of degrees of freedom and exhibit some time-varying or nonlinear behavior, especially under extreme excitation or when damaged. In this study, an offline substructure method based on wavelet multiresolution approximation (WMRA) is proposed for the identification of arbitrary time-varying parameters in a shear-beam building. Assuming that the possible damage location of the building can be identified a priori, a substructural model containing both interface and internal restoring forces can be formulated. The WMRA can then be used to approximate the time-varying damping and stiffness parameters and convert a time-varying parametric identification problem into a time-invariant coefficient estimation problem. To obtain accurate estimation and minimize the computational effort, Akaike's information criterion is used for the selection of a resolution level and the pruning of insignificant terms. Numerical and experimental results show that the proposed technique can locate and quantify the time-varying parameters in the substructure. The method inherits the wavelet's excellent capability in the approximation of arbitrary functions and provides a flexible approach for identifying various types of time-varying parameters in shear-beam buildings.

Original languageEnglish
Pages (from-to)50-59
Number of pages10
JournalJournal of Engineering Mechanics
Volume138
Issue number1
DOIs
Publication statusPublished - 30 Jul 2011
Externally publishedYes

Keywords

  • Substructural technique
  • Time-varying system identification
  • Wavelet multiresolution approximation

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