Prognostics CoE Publications

Real-time measurements of the structural performance are now possible through state-of-the-art structural health monitoring (SHM) techniques, and a large amount of response data can be readily acquired and further analyzed to assess various health-related properties of structures. Therefore, a suitable approach for fatigue damage prediction is through the use of monitored response of the structure to update a given damage model so as to make more accurate predictions that also account for uncertainty. Development of such SHM-based damage prognostics approach is the core objective of this chapter. In particular, a model-based prognostics framework is proposed to predict a sequence of damage states of composite laminates subjected to fatigue loading. Damage states as well as model parameters of the underlying damage model are sequentially updated and predicted based on available SHM data. The proposed methodology is implemented and demonstrated using data for microcrack density and stiffness reduction in carbon fiber reinforced plastic (CFRP) cross-ply laminates from run-to-failure tension fatigue experiments.