000012139 001__ 12139
000012139 005__ 20141205160023.0
000012139 04107 $$aeng
000012139 046__ $$k2008-10-12
000012139 100__ $$aXu, Bin
000012139 24500 $$aValidation of an Identification Methodology for a Model Frame Structure on Shaking Table Using Laser Displacement Sensing

000012139 24630 $$n14.$$pProceedings of the 14th World Conference on Earthquake Engineering
000012139 260__ $$b
000012139 506__ $$arestricted
000012139 520__ $$2eng$$aFor the purpose of health monitoring, post-earthquake condition evaluation and safety appraisal of existing infrastructures, many structural parameter identification methodologies based on eigenvalue and/or mode shape extraction from structural vibration measurement have been proposed. In this study, a general structural parameter identification strategy based on neural networks is proposed and the theoretical base for the construction of a neural network emulator(NNE) and a parametric evaluation neural network(PENN) is explained. A two-story model frame structure on a shaking table is employed as an illustrative structure to validate the performance of the proposed approach for structural stiffness identification and damage detection using vibration displacement response measurement from laser displacement sensors. Results show that the NNE can forecast the displacement of the reference structure with high accuracy, and PENN can describe the mapping between an evaluation index and structural stiffness parameter. Compared with results that from traditional identification method based on frequencies extraction, the performance of the proposed methodology is validated. The proposed algorithm is a general and applicable way in practice for near real-time identification, damage detection and structural model updating.

000012139 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000012139 653__ $$aparameter identification, damage detection, neural network, time series, laser displacement sensor

000012139 7112_ $$a14th World Conference on Earthquake Engineering$$cBejing (CN)$$d2008-10-12 / 2008-10-17$$gWCEE15
000012139 720__ $$aXu, Bin$$iZhang, Lili$$iSong, Gangbing
000012139 8560_ $$ffischerc@itam.cas.cz
000012139 8564_ $$s174567$$uhttps://invenio.itam.cas.cz/record/12139/files/14-0161.pdf$$yOriginal version of the author's contribution as presented on CD, Paper ID: 14-0161.
000012139 962__ $$r9324
000012139 980__ $$aPAPER