Condensed Model Identification and Recovery for Structural Damage Assessment

Abstract

This study aims to develop a system identification methodology for determining structural parameters of linear dynamic system, taking into consideration of practical constraints such as insufficient sensors. A new methodology called the condensed model identification and recovery method is presented for identification of full stiffness matrices for damage assessment based on incomplete measurement. With the proposed methodology, it is possible to obtain several condensed stiffness matrices, so as to identify individual stiffness coefficients for the structure. Three different model condensation methods, namely static condensation, dynamic condensation, and system equivalent reduction expansion process, are adopted. Having identified the condensed model, the stiffness parameters in the entire system are recovered by extracting sufficient information with either fixed sensor or repositioned sensor approach. The efficiency of the proposed technique is shown by numerical simulation study for multistory shear buildings subjected to random forces, accounting for effects of signal noise. In addition, laboratory experiments are carried out to illustrate the performance of the proposed method. It is shown both numerically and experimentally that the proposed methodology gives reasonably accurate identification in terms of locating and quantifying structural damage.