This paper studies the possibility of using measured transient vibration data in the detection of multiple cracks on beams by following the Bayesian probabilistic framework. The proposed method adopts different classes of models in modelling a beam with different numbers of cracks. The number of cracks on the beam can then be identified by calculating the probability of a model class conditional on a given set of measured transient vibration data. By following the Bayesian probabilistic framework, the posterior probability density functions (PDFs) for a set of crack parameters, such as the crack locations and the corresponding extents, can be calculated. The PDFs allow engineers to quantify the uncertainties associated with the results of crack detection. The paper reports not only the theoretical developed but also the experimental verification of the proposed method
