A probabilistic crack size quantification method using in-situ Lamb wave test and Bayesian updating

Abstract

This paper presents a new crack size quantification method based on in-situ Lamb wave testing and Bayesian method. The proposed method uses coupon test to develop a baseline quantification model between the crack size and damage sensitive features. In-situ Lamb wave testing data on actual structures are used to update the baseline model parameters using Bayesian method to achieve more accurate crack size predictions. To demonstrate the proposed method, Lamb wave testing on simple plates with artificial cracks of different sizes is performed using surface-bonded piezoelectric wafers, and the data are used to obtain the baseline model. Two damage sensitive features, namely, the phase change and normalized amplitude are identified using signal processing techniques and used in the model. To validate the effectiveness of the method, the damage data from an in-situ fatigue testing on a realistic lap-joint component are used to update the baseline model using Bayesian method.