000010590 001__ 10590
000010590 005__ 20141205155743.0
000010590 04107 $$aeng
000010590 046__ $$k2008-10-12
000010590 100__ $$aKuroiwa, Tatiana
000010590 24500 $$aVibration-Based Damage Detection Using Time Series Analysis

000010590 24630 $$n14.$$pProceedings of the 14th World Conference on Earthquake Engineering
000010590 260__ $$b
000010590 506__ $$arestricted
000010590 520__ $$2eng$$aIn this paper, a statistical pattern recognition method based on time series analysis is implemented to a 5 Story steel frame model. This method uses a combination of Auto-Regressive (AR) and Auto-Regressive with eXogenous inputs (ARX) prediction models. The response of the system was obtained for a linear system subjected to white-noise input. The standard deviation of Mahalanobis squared distance between healthy and damaged state is used to locate structural damaged sites. Three damage scenarios were studied. The occurrences and location of damage were identified for all cases.

000010590 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000010590 653__ $$adamage detection, structural health monitoring, vibration-based method, time series analysis

000010590 7112_ $$a14th World Conference on Earthquake Engineering$$cBejing (CN)$$d2008-10-12 / 2008-10-17$$gWCEE15
000010590 720__ $$aKuroiwa, Tatiana$$iIemura, Hirokazu
000010590 8560_ $$ffischerc@itam.cas.cz
000010590 8564_ $$s493671$$uhttps://invenio.itam.cas.cz/record/10590/files/12-01-0130.pdf$$yOriginal version of the author's contribution as presented on CD, Paper ID: 12-01-0130.
000010590 962__ $$r9324
000010590 980__ $$aPAPER