Damage Classification of Sandwich Composites Using Acoustic Emission Technique and k-means Genetic Algorithm

摘要

In this study acoustic emission (AE) technique was used for monitoring mode I delamination test of sandwich composites. Since, during mode I delamination test various damage mechanisms appear, their classification is of major importance. Hence, integration of -means algorithm and genetic algorithm was applied as an efficient clustering method to discriminate different failure modes. Performing primary experiments to find the relationship between AE parameters and damage mechanisms, the AE signals of obtained clusters were assigned to distinct damage mechanisms. Also, the dominance of damage mechanisms was determined based on the distribution of AE signals in different clusters. Finally SEM observation was employed to verify obtained results. The results indicate the efficiency of the proposed method in damage classification of sandwich composites.