A recursive Bayesian framework for structural health management using online monitoring and periodic inspections

The necessary information for developing a structural health diagnostic and prognostic solution is often obtained from various sources. This paper presents a Bayesian framework for online integration of the structural health assessment information obtained from empirical crack growth models, structural health monitoring and periodic inspections. The data used in Bayesian updating could be direct damage observations (e.g., observed crack sizes) and/or damage growth rate estimates (e.g., crack growth rate observations). An AE-based monitoring approach is used to obtain the crack growth rate observations in this paper. The outcome of this approach is updated crack size distribution as well as updated parameters for an empirical crack growth model. The model with updated parameters is used for prognosis given an assumed future usage profile.