Abstract
AbstractThe robustness of Non-Destructive Testing methods is typically quantified through the computation of Probability of Detection (POD) curves. Current design standards in aviation recommend the implementation of these curves also for Guided Waves based Structural Health Monitoring (GWSHM) systems. POD curves are greatly influenced by the uncertainties that may exist within the SHM acquisition due to operational and environmental conditions. These uncertainties play a particularly important role in the detection of Barely Visible Impact Damage (BVID) in complex composite structures. In this work, a digital clone platform that is created with the aid of a Bayesian calibration of a Finite Element (FE) model, is used to complement the experimental measurements. Based on the estimations of the platform it is possible to generate a numerical sample of impact events that allows the estimation of the Model Assisted Probability of Detection (MAPOD), considering the underlying uncertainties. The performance of the proposed framework is evaluated for a surface mounted network of sensors that is permanently attached onto a composite structure.KeywordsStructural Health MonitoringFinite element modellingDamage detectionBayesian calibrationUncertainty propagation
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