Guided wave-based identification of multiple cracks in beams using a Bayesian approach

A guided wave damage identification method using a model-based approach is proposed to identify multiple cracks in beam-like structures. The guided wave propagation is simulated using spectral finite element method and a crack element is proposed to take into account the mode conversion effect. The Bayesian model class selection algorithm is employed to determine the crack number and then the Bayesian statistical framework is used to identify the crack parameters and the associated uncertainties. In order to improve the efficiency and ensure the reliability of identification, the Transitional Markov Chain Monte Carlo (TMCMC) method is implemented in the Bayesian approach. A series of numerical case studies are carried out to assess the performance of the proposed method, in which the sensitivity of different guided wave modes and effect of different levels of measurement noise in identifying different numbers of cracks is studied in detail. The proposed method is also experimentally verified using guided wave data obtained from laser vibrometer. The results show that the proposed method is able to accurately identify the number, locations and sizes of the cracks, and also quantify the associated uncertainties. In addition the proposed method is robust under measurement noise and different situations of the cracks.