Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

In this study, a multi-level Structural Health Monitoring methodology for stiffened composite panels is introduced. A digital twin (DT), that is, a three-dimensional finite element (FE) model, representing the pristine state baseline of the test article, is developed and verified for compressive loading in the post-buckling regime. The detailed FE model is utilized to train a surrogate model with respect to exogenous input, that is, axial load magnitude. The surrogate assists the DT concept that would allow prediction of the load acting on the structure based on an influx of strain data, acquired from fiber Bragg grating sensors permanently attached along the stringer feet. For this purpose, we leverage on the observation that remote from the damage, the strain field remains virtually unaltered with regard to the pristine state. The load is estimated by a sensor placed far from the damage whilst the diagnostic actions are performed by exploiting measurements from the remaining sensing locations. A health indicator, which compares the experimentally received strains with those from the surrogate representing the pristine state, is utilized to (1) detect, (2) localize, and (3) characterize the damage. As damage, we consider either skin-to-stringer disbond or initial impact damage propagation as well as overall stiffness degradation during thousands or millions of fatigue cycles. The sensors that have detected a disbond are dedicated to evaluating the potential propagation of it, while the remaining sensors evaluate the overall stiffness degradation. The proposed methodology is tested for one artificially disbonded and two impacted single-stringer panels subjected to block loading compression-compression fatigue.