Vibration-Based Seismic Damage Identification in Buildings

José L. Zapico; María P. González

doi:10.4028/www.scientific.net/KEM.293-294.727

Paper Titles

Ultrasonic Damage Measurement in Reinforced Concrete Beams
p.695

Instantaneous Identification of Polynomial Nonlinearity Based on Volterra Series Representation
p.703

Impact Force Spectrum for Damage Assessment of Earthquake-Induced Structural Pounding
p.711

Local and Global Damages of Quasi-Brittle Material in Uniaxial Compression Based on Gradient-Dependent Plasticity
p.719

Vibration-Based Seismic Damage Identification in Buildings
p.727

Modal Analysis of a Reinforced Concrete Frame in Various States of Damage
p.735

Vibration-Based Condition Monitoring of Smart Prefabricated Concrete Elements
p.743

Detecting Damage of Rolling Bearings Using EMD
p.753

Prediction of the Influence of Vibration on Structural Integrity of Elevator Suspension Ropes
p.761

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Vibration-Based Seismic Damage Identification in Buildings

Abstract:

This article deals with a method for seismic damage identification in buildings with steel moment-frame structure. The damage identification is based on artificial neural networks and natural frequencies. A simplified finite element model is used to obtain the data needed for training the nets. The method is simulated on a four-storey building under conditions as close as possible to reality. The robustness of the method and its sensitivity to the variations of the mass with time and the influence of the data errors is addressed. The statistical analysis of the results is successful, but it reveals that the predictions are quite sensitive to the data errors.