Model-Based Prognosis for Remaining Useful Life Prediction of Composite Components

Prognostics of composite structures is a key issue in the structural health monitoring of automotive, aerospace, and mechanical systems. In order to predict the remaining useful life (RUL) of composite structures, especially, we focused on the analysis of lower control arm (LCA), which is laminated at various angles with carbon fiber reinforced plastic (CFRP), as a component under severe load conditions. LCA model is shape optimized by applying the CFRP material to the conventional LCA shape, and the damage model according to the fatigue cycle is obtained by integrating the simulation technique and fatigue characteristics of CFRP. Model-based approach includes uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process for predicting the matrix crack evolution and structural stiffness degradation caused by fatigue loads. Then, Bayesian inference is employed to estimate model parameters characterizing the damage behavior using measurement data. As a result, the RUL of CFRP LCA is calculated based on the estimated model parameters associated with uncertainties.