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Title: A coupled approach of spatial dielectric mapping and unsupervised machine learning for damage detection and severity segmentation in polymer matrix composites
The inevitable presence of moisture within a polymer composite has allowed for the development of a novel dielectric nondestructive evaluation (NDE) technique which capitalizes on the behavior of moisture under an applied electromagnetic field. Relative permittivity of water which is bound to the polymer network differ significantly from that of water which is not bound to the network, and the preferential diffusion of this “free” water to damage sites permits the creation of spatial permittivity maps. Presently, this technique has shown capability for damage detection but has not achieved quantification, which is crucial for industry use. The introduction of machine learning algorithms to existing techniques in this field has proven valuable, thus, a machine learning approach for data processing and damage quantification to the existing dielectric technique was developed and applied in this work. BMI/Quartz samples and S2-Glass/Epoxy samples were fabricated and subjected to impact damage via drop tower. The BMI samples were impacted centrally at 9 J and the S2-Glass samples were subjected to two impact events of differing energies, 5 and 3 J. An unsupervised K-means clustering algorithm was applied to the acquired dielectric scans at different gravimetric moisture contents which has provided promising results for all samples. Specifically, within the two impact samples, the algorithm assigned a higher cluster center to the site with more damage, indicating the technique has the capability to both detect and quantify impact damage at all moisture levels examined.  more » « less
Award ID(s):
1751482
NSF-PAR ID:
10536046
Author(s) / Creator(s):
; ;
Publisher / Repository:
Elsevier
Date Published:
Journal Name:
NDT & E International
Volume:
145
Issue:
C
ISSN:
0963-8695
Page Range / eLocation ID:
103137
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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