Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

Composite structures are gaining importance in the aerospace industry; however, uncertain structural integrity due to fatigue under continuous usage is a big concern. It is arguably possible to detect precursors of failures as damage progresses and can be used to predict impending failures. Prognostic algorithms require large amounts of training data to build damage model for making useful predictions. One of the key aspects in these data is the trends of damage progression. Since these data are rarely available from actual systems an accelerated aging platform is the next possible resource to collect such data. A fatigue cycling experiment was designed to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis has shown distinct differences in the signatures of growing failures between data collected at conditions. Periodic Xradiographs were taken to assess the damage ground truth. Results from signal processing shows clear trends of damage growth in these coupons that were correlated to damage assessed from the X-ray images. Results from the analysis are presented in this paper.