TY - JOUR
T1 - Clustering of interlaminar and intralaminar damages in laminated composites under indentation loading using Acoustic Emission
AU - Saeedifar, Milad
AU - Najafabadi, Mehdi Ahmadi
AU - Zarouchas, Dimitrios
AU - Toudeshky, Hossein Hosseini
AU - Jalalvand, Meisam
PY - 2018/7/1
Y1 - 2018/7/1
N2 - This study focuses on the clustering of the indentation-induced interlaminar and intralaminar damages in carbon/epoxy laminated composites using Acoustic Emission (AE) technique. Two quasi-isotropic specimens with layups of [60/0/-60]4S (is named dispersed specimen) and [604/04/-604]S (is named blocked specimen) were fabricated and subjected to a quasi-static indentation loading. The mechanical data, digital camera and ultrasonic C-scan images of the damaged specimens showed different damage evolution behaviors for the blocked and dispersed specimens. Then, the AE signals of the specimens were clustered for tracking the evolution behavior of different damage mechanisms. In order to select a reliable clustering method, the performance of six different clustering methods consisting of k-Means, Genetic k-Means, Fuzzy C-Means, Self-Organizing Map (SOM), Gaussian Mixture Model (GMM), and hierarchical model were compared. The results illustrated that hierarchical model has the best performance in clustering of AE signals. Finally, the evolution behavior of each damage mechanism was investigated by the clustered AE signals with hierarchical model. The results of this study show that using AE technique with an appropriate clustering method such as hierarchical model could be an applicable tool for structural health monitoring of composite structures.
AB - This study focuses on the clustering of the indentation-induced interlaminar and intralaminar damages in carbon/epoxy laminated composites using Acoustic Emission (AE) technique. Two quasi-isotropic specimens with layups of [60/0/-60]4S (is named dispersed specimen) and [604/04/-604]S (is named blocked specimen) were fabricated and subjected to a quasi-static indentation loading. The mechanical data, digital camera and ultrasonic C-scan images of the damaged specimens showed different damage evolution behaviors for the blocked and dispersed specimens. Then, the AE signals of the specimens were clustered for tracking the evolution behavior of different damage mechanisms. In order to select a reliable clustering method, the performance of six different clustering methods consisting of k-Means, Genetic k-Means, Fuzzy C-Means, Self-Organizing Map (SOM), Gaussian Mixture Model (GMM), and hierarchical model were compared. The results illustrated that hierarchical model has the best performance in clustering of AE signals. Finally, the evolution behavior of each damage mechanism was investigated by the clustered AE signals with hierarchical model. The results of this study show that using AE technique with an appropriate clustering method such as hierarchical model could be an applicable tool for structural health monitoring of composite structures.
KW - Acoustic emission
KW - Clustering methods
KW - Damage mechanisms
KW - Indentation loading
KW - Laminated composites
UR - http://www.scopus.com/inward/record.url?scp=85043453098&partnerID=8YFLogxK
U2 - 10.1016/j.compositesb.2018.02.028
DO - 10.1016/j.compositesb.2018.02.028
M3 - Article (Academic Journal)
AN - SCOPUS:85043453098
SN - 1359-8368
VL - 144
SP - 206
EP - 219
JO - Composites Part B: Engineering
JF - Composites Part B: Engineering
ER -