Damage monitoring in fibre-reinforced polymer composites using adaptive threshold methods and geometric features

• Published in: Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 45; no. 1
• Main Authors: Kotha, Rohan, Rani, Priya, Robert, Femi, Thomas, Christy Bobby, Chelliah, Suresh Kumar, Agastinose Ronickom, Jac Fredo
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2023; Springer Nature B.V
• Subjects: Aerospace industry; Digital imaging; Engineering; Fiber composites; Fiber reinforced polymers; Glass fiber reinforced plastics; Image acquisition; Impact damage; Impact resistance; Indentation; Laminar composites; Mechanical Engineering; Polymer matrix composites; Technical Paper; GFRP composites; Geometric features; Dent depth; Impact damage; Adaptive thresholding
• ISSN: 1678-5878; 1806-3691
• DOI: 10.1007/s40430-022-03931-y

Laminated composites are prone to impact-induced damage during their service operations, which is significant to assess the extent of damage. This study proposes a framework to assess the intensity of impact-induced damage in composites using digital image correlation (DIC) technique. Initially, glass fibre-reinforced polymer (GFRP) composite specimens were subjected to different indentation displacements of 5, 6 and 7 mm, and digital images were acquired on the front and rear sides of the indented specimens. Images are pre-processed using median and Gaussian filters, and their results were compared. Damage regions are segmented through Gaussian threshold (AGT) and adaptive mean threshold (AMT) methods, and the extent of damage was calculated using geometrical features. Pre-processing results show that the Gaussian filter performs better than the median filter. It was also found that AGT and AMT methods performed equally well in segmenting the damaged zone. Geometric features such as area and perimeter were able to quantify the induced damage under different indentation displacements. The result shows a better correlation ( R  = 0.85) between the dent depth and rear surface area obtained from the AGT segmented damage regions. This framework produces higher performance with simple instrumentation facilities; thus, it can be implemented in aerospace and automobile industries to evaluate the impact damage resistance in various structural components.