Experimental Verification of Substructure Identification for Damage Detection in Shear Buildings

Abstract

AbstractDamage detection for civil structures is limited by several factors including poor signal-to-noise ratios, a large number of unknown parameters, and a limited set of measured responses. Global vibration techniques that track modal parameters often remain insensitive to common forms of structural damage. Moreover, large sets of identified parameters make inverse problems ill-conditioned. To overcome some of these limitations, researchers have advanced substructure identification as a methodology to directly detect local stiffness changes using measured responses to improve damage detection and scalability in civil structures. This paper develops a substructure identification estimator that identifies the story stiffness of a shear building. Concurrent with the estimator derivation, identified parameter confidence intervals are developed and identification performance is predicted. Using the developed estimator, experimental testing is performed on a 3.66-m (12-ft) four-story steel structure subject...