TOF-based fuzzy C-means clustering method for tomographic evaluation of impact damage in CFRP laminates

Impact damage in carbon-fibre-reinforced polymer (CFRP) laminates threatens the safety of their structures, making it necessary to perform non-destructive testing (NDT) to avoid catastrophic accidents. In this study, a TOF-based fuzzy C-means (FCM) clustering method was developed for the tomographic evaluation of impact damage in CFRP laminates. Ultrasound water immersion experiments were conducted to obtain the time-of-flight (TOF) features of the CFRP laminates with different impact energies. To avoid the limitations of common FCM clustering methods, such as easily falling into local optimal solutions, the initial clustering centres were determined based on the most frequently occurring TOF values across all spatial points. The feasibility of the proposed TOF-based FCM was further validated using X-ray computed tomography (CT) experiments. Moreover, its applicability was demonstrated in CFRP laminates with more complex stacking sequences. The clustering performance of the proposed method was compared with that of Multi-Otsu, K-means, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). Among these approaches, FCM with the most frequent initialisation achieved a relatively high clustering accuracy while maintaining a low computation time, suggesting a favourable balance between precision and efficiency.