Abstract: The paper presents a methodology for identification of localized structural damage using highly incomplete modal information, such as a subset of modal frequencies. The proposed methodology is based on linearized modal ...

Abstract: The paper presents a methodology for identification of localized structural damage using highly incomplete modal information, such as a subset of modal frequencies. The proposed methodology is based on linearized modal ...

Abstract: The l1-norm regularized inverse methods have been suggested as a means to quantify and localize spatially sparse damage from a set of identified natural frequencies. Thus far, damage has been interpreted as changes in ...

Abstract: This paper presents a probabilistic framework for estimating seismic-induced damage in partially instrumented buildings. The proposed framework uses acceleration measurements at a limited number of stories and Bayesian ...

Abstract: This paper presents the application of Bayesian filtering for the estimation and uncertainty quantification of interstory drifts and shears in partially instrumented buildings. We investigate the performance of four Bayesian ...

Abstract: This paper presents the application of Bayesian filtering for the estimation and uncertainty quantification of interstory drifts and shears in partially instrumented buildings. We investigate the performance of four Bayesian ...

Abstract: This paper presents an observer designed under the assumption that differences between predicted and measured outputs arise from discrepancies between the real structural system and the nominal model used to represent it. ...

Abstract: The authors propose a seismic monitoring framework for instrumented buildings that employs dissipated energy as a feature for damage detection and localization. The proposed framework employs a nonlinear model-based state ...