Buckypaper embedded self-sensing composite for real-time fatigue damage diagnosis and prognosis

Abstract

In this study, buckypaper (BP) membranes have been used to introduce self-sensing capability in glass fiber reinforced polymer matrix (GFRP) laminates by embedding them in the interlaminar region of the laminates. Piezoresistive characterization studies were conducted by subjecting the self-sensing GFRP (SGFRP) specimens to cyclic loading and high sensitivity to strain was observed. A measurement model for real-time quantification of fatigue crack, developed using in-situ resistance measurements obtained under fatigue loading, was used to quantify fatigue crack length in real time. The fatigue crack growth rates and the nature of crack propagation in baseline and SGFRP specimens were compared. The results show that the introduction of BP reduced the average crack growth rate by an order of magnitude as a result of crack tip blunting during fatigue, while facilitating real time strain sensing and damage quantification. A fully probabilistic prognosis methodology was also developed by combining the in-situ measurement model with a machine learning based prognosis model to accurately predict the real-time fatigue crack propagation using sequential Bayesian techniques.