Fibre-Reinforced Self-Healing Composites: Mechanical Characterisation using Acoustic Emission Technique

The autonomous healing of polymeric matrices in the fibre-reinforced composites has received significant attention in recent years. This research investigates the ability of an intrinsically healable polymer resin to heal internal defects in a fibre-dense composite. Unstable internal defects are created in a self-healing Carbon Fibre-Reinforced Polymer composites (CFRPs) using a three-point bending setup. Mild heat is applied as an external stimulus to heal the damaged composites. Mechanical performance recovery is evaluated by testing the virgin, damaged, and healed composites under flexural loads. The test results reveal a marginal recovery of flexural properties after healing. The damage progression in the composites, as well as the rationale behind this marginal recovery of the flexural properties are evaluated using Acoustic Emission (AE) tests. Machine Learning (ML)-based unsupervised data clustering and Continuous Wavelet Transform (CWT) are employed to analyse the parameter-based and signal-based AE data, respectively. The results are further validated using microscopic analysis. These results suggest that the healing process has altered the damage progression path in the self-healing CFRPs and is responsible for the recovery of flexural properties.