000189140 001__ 189140
000189140 005__ 20190316235716.0
000189140 0247_ $$2doi$$a10.1016/j.ymssp.2012.05.017
000189140 022__ $$a0888-3270
000189140 02470 $$2ISI$$a000319232200015
000189140 037__ $$aARTICLE
000189140 245__ $$aHybrid probabilities and error-domain structural identification using ambient vibration monitoring
000189140 260__ $$bElsevier$$c2013$$aLondon
000189140 269__ $$a2013
000189140 300__ $$a14
000189140 336__ $$aJournal Articles
000189140 520__ $$aFor the assessment of structural behaviour, many approaches are available to compare model predictions with measurements. However, few approaches include uncertainties along with dependencies associated with models and observations. In this paper, an error-domain structural identification approach is proposed using ambient vibration monitoring (AVM) as the input. This approach is based on the principle that in science, data cannot truly validate a hypothesis, it can only be used to falsity it. Error-domain model falsification generates a space of possible model instances (combination of parameters), obtains predictions for each of them and then rejects instances that have unlikely differences (residuals) between predictions and measurements. Models are filtered in a two step process. Firstly a comparison of mode shapes based on MAC criterion ensures that the same modes are compared. Secondly, the frequencies from each model instance are compared with the measurements. The instances for which the difference between the predicted and measured value lie outside threshold bounds are discarded. In order to include "uncertainty of uncertainty" in the identification process, a hybrid probability scheme is also presented. The approach is used for the identification of the Langensand Bridge in Switzerland. It is used to falsify the hypothesis that the bridge was behaving as designed when subjected to ambient vibration inputs, before opening to the traffic. Such small amplitudes may be affected by low-level bearing-device friction. This inadvertently increased the apparent stiffness of the structure by 17%. This observation supports the premiss that ambient vibration surveys should be cross-checked with other information sources, such as numerical models, in order to avoid misinterpreting the data. (C) 2012 Elsevier Ltd. All rights reserved.
000189140 6531_ $$aStructural identification
000189140 6531_ $$aAmbient vibration monitoring
000189140 6531_ $$aUncertainty
000189140 6531_ $$aError-domain identification
000189140 6531_ $$aExtended uniform distribution
000189140 6531_ $$aCorrelation
000189140 700__ $$0242295$$g184665$$uEcole Polytech Fed Lausanne, Sch Architecture Civil & Environm Engn ENAC, Appl Comp & Mech Lab IMAC, CH-1015 Lausanne, Switzerland$$aGoulet, James-A.
000189140 700__ $$aMichel, Clotaire
000189140 700__ $$uEcole Polytech Fed Lausanne, Sch Architecture Civil & Environm Engn ENAC, Appl Comp & Mech Lab IMAC, CH-1015 Lausanne, Switzerland$$aSmith, Ian F. C.$$g106443$$0241981
000189140 773__ $$j37$$tMechanical Systems And Signal Processing$$k1-2$$q199-212
000189140 8564_ $$uhttps://infoscience.epfl.ch/record/189140/files/Goulet_et_al-Postprint-dynamic_2013.pdf$$zn/a$$s7989935$$yn/a
000189140 909C0 $$xU10237$$0252031$$pIMAC
000189140 909CO $$qGLOBAL_SET$$particle$$ooai:infoscience.tind.io:189140$$pENAC
000189140 917Z8 $$x106443
000189140 917Z8 $$x106443
000189140 937__ $$aEPFL-ARTICLE-189140
000189140 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000189140 980__ $$aARTICLE