Crack detection of beam-type structures following the bayesian system identification framework

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

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Original languageEnglish
Article number12030
Journal / PublicationJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 2008


Title4th Applied Inverse Problems International Conference, AIP 2007 and the 1st Congress of the Inverse Problems International Association, IPIA 2007
CityVancouver, BC
Period25 - 29 June 2007


This paper puts forward a method for the detection of crack locations and extents on a structural member utilizing measured dynamic responses following the Bayesian probabilistic framework. In the proposed crack detection method a beam with different number of cracks is modelled using different classes of models. The Bayesian model class selection method is then applied to select the "most plausible" class of models in order to identify the number of cracks on the structural member. The objective of the proposed method is not to pinpoint the crack locations and extents but to calculate the posterior (updated) probability density function (PDF) of crack parameters (i.e., crack locations and extents). The method explicitly handles the uncertainties introduced by measurement noise and modelling error. This paper presents not only the theoretical development of the proposed method but also the numerical and experimental verifications. In the numerical case studies, noisy data generated by a Bernoulli-Euler beam with semi-rigid connections is used to demonstrate the procedures of the proposed method. The method is finally verified by measured dynamic responses of a cantilever beam utilizing laser Doppler vibrometer. © 2008 IOP Publishing Ltd.