000022150 001__ 22150
000022150 005__ 20170622145959.0
000022150 04107 $$aeng
000022150 046__ $$k2015-05-25
000022150 100__ $$aPaul, Prodip K.
000022150 24500 $$aSYSTEM IDENTIFICATION AND DAMAGE DETECTION OF R.C. STRUCTURE

000022150 24630 $$n5.$$pComputational Methods in Structural Dynamics and Earhquake Engineering
000022150 260__ $$bNational Technical University of Athens, 2015
000022150 506__ $$arestricted
000022150 520__ $$2eng$$aEvaluation of system parameters of civil engineering structures using system identification techniques has attracted considerable attention in recent years. Recorded dynamic responses of the structures due to ambient or earthquake excitations are utilized for identification of system parameters of the structures. Huge amount of works have been carried out in the field of linear time invariant system identification; but the application in time varying system identification is very limited. In the present study, three numbers of numerically simulated models of 1/5th scaled bare frame two storey R.C. buildings have been considered. Nonlinear time history analyses are carried out to detect the changes of modal parameters of the deteriorating structure. Further, acceleration responses are collected from different floors during base excitation of models. Linear Deterministic-Stochastic Identification (DSI) technique (e.g. N4SID) is then used for the identification of modal parameters (natural frequency). Since, a linear DSI algorithm would not be applicable for structures excited to nonlinear range, hence modal parameters are obtained for short data time windows. These instantaneous modal parameters are found to represent the deterioration of the structure reasonably well. Further, an approach referred to as the sequential non-linear least-square estimation (SNLSE) is used to compare the identified result obtained from N4SID algorithm using short time data window. In this approach, acceleration responses and external excitations are measured, whereas the structural parameters and response state vector are estimated similar to the Extended Kalman Filter (EKF) approach. It is superior to EKF in terms of stability and convergence.

000022150 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000022150 653__ $$aNonlinear system identification, instantaneous modal parameters, N4SID, Sequential nonlinear least square estimation, damage detection.

000022150 7112_ $$aCOMPDYN 2015 - 5th International Thematic Conference$$cCrete (GR)$$d2015-05-25 / 2015-05-27$$gCOMPDYN2015
000022150 720__ $$aPaul, Prodip K.$$iDeb, Sajal K.$$iDutta, Anjan
000022150 8560_ $$ffischerc@itam.cas.cz
000022150 8564_ $$s945648$$uhttps://invenio.itam.cas.cz/record/22150/files/C1338.pdf$$yOriginal version of the author's contribution as presented on CD, section: 
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000022150 962__ $$r22030
000022150 980__ $$aPAPER