Abstract

This study presents a Lamb wave-based structural health monitoring method for aircraft riveted lap joint. Lamb wave data of lap joint are processed and damage features are extracted to formulate crack quantification models. Four quantification models are proposed and studied. Probability of detection (POD) modeling is employed to provide a distribution of the actual crack size using the quantification model. Paris' model is used to characterize crack propagation. Bayesian method and Markov Chain Monte Carlo (MCMC) simulation are used to estimate the model parameters upon measurement data of lap joint. Results show predicted probabilistic fatigue life of lap joint is accurate.

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