Share Email Print

Proceedings Paper

Correlation between damage detection and observed damage for a full-scale four-story steel building during the collapse test
Author(s): Liu Mei; Akira Mita
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A full-scale four-story steel building was tested on the shaking table of the E-defense project on September, 2007. During the shaking table tests, the building was damaged progressively through various levels of seismic excitations, and finally collapsed on the first floor. To evaluate the modal parameters, low-amplitude white noise excitations were applied to the building and the response of the building was measured at various levels of damage due to the seismic excitations. The subspace identification method is then applied to identify the modal parameters of the building based on the measured data. This paper focuses on detecting damage of this building based on changes in identified modal parameters. A finite element model updating strategy is applied to identify (detect, localize and quantify) the damage in the building at each damage state considered. The residuals used in the updating procedure are based on the identified natural frequencies and mode shapes for the first two X direction and Y direction vibration modes of the building. At last the correlation between the damage detection results and the actual damage observed in the building is carefully examined. They do not exactly coincide but the concentration regions of damage are highly consistent with each other.

Paper Details

Date Published: 18 April 2011
PDF: 11 pages
Proc. SPIE 7984, Health Monitoring of Structural and Biological Systems 2011, 79842N (18 April 2011); doi: 10.1117/12.880211
Show Author Affiliations
Liu Mei, Keio Univ. (Japan)
Akira Mita, Keio Univ. (Japan)

Published in SPIE Proceedings Vol. 7984:
Health Monitoring of Structural and Biological Systems 2011
Tribikram Kundu, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?