Substructural Time-Varying Parameter Identification Using Wavelet Multiresolution Approximation

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 i...

[1]  David A. Nix,et al.  Vibration–based structural damage identification , 2001, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[2]  A. Smyth,et al.  Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurement in dynamic system monitoring , 2007 .

[3]  Jann N. Yang,et al.  Identification of Parametric Variations of Structures Based on Least Squares Estimation and Adaptive Tracking Technique , 2005 .

[4]  Chung Bang Yun,et al.  Substructural identification using neural networks , 2000 .

[5]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[6]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[7]  Tsutomu Sawada,et al.  Localized identification of MDOF structures in the frequency domain , 1995 .

[8]  Y. Wen.  Method for Random Vibration of Hysteretic Systems , 1976 .

[9]  Richard W. Longman,et al.  On‐line identification of non‐linear hysteretic structural systems using a variable trace approach , 2001 .

[10]  Chih-Chen Chang,et al.  IDENTIFICATION OF TIME-VARYING HYSTERETIC STRUCTURES USING WAVELET MULTIRESOLUTION ANALYSIS , 2010 .

[11]  Steve A. Billings,et al.  Identification of Time-Varying Systems Using Multiresolution Wavelet Models , 2003 .

[12]  L. M. See,et al.  Estimation of structural parameters in time domain: A substructure approach , 1991 .

[13]  Sheng Chen,et al.  Orthogonal least squares methods and their application to non-linear system identification , 1989 .

[14]  Jann N. Yang,et al.  Damage identification of substructure for local healthmonitoring , 2008 .

[15]  H. Adeli,et al.  Dynamic Fuzzy Wavelet Neural Network Model for Structural System Identification , 2006 .

[16]  Pol D. Spanos,et al.  Wavelets : Theoretical concepts and vibrations related applications , 2005 .

[17]  H. Akaike.  A new look at the statistical model identification , 1974 .

[18]  R. Ghanem,et al.  A WAVELET-BASED APPROACH FOR THE IDENTIFICATION OF LINEAR TIME-VARYING DYNAMICAL SYSTEMS , 2000 .

[19]  Chih-Chen Chang,et al.  Nonlinear Identification of Lumped-Mass Buildings Using Empirical Mode Decomposition and Incomplete Measurement , 2010 .