4.7 Article

Delamination measurement in glass fibre reinforced polymer (GFRP) composite based on image differencing*

Journal

COMPOSITES PART B-ENGINEERING
Volume 248, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesb.2022.110381

Keywords

Polymer -matrix composites; Delamination; Optical microscopy; Machining

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This research develops a drilling-induced delamination measurement method in fibrous polymeric composites based on the image differentiation principle. It can effectively distinguish drilling-induced delamination from other material defects, and has a wide range of applications.
Drilling-induced delamination is the most severe material defect in fibrous polymeric composites. Although many delamination measurement methods are available, the outputs of recent digital image processing (DIP) based delamination measurement methods are significantly affected by the non-drilling induced material defects and anomalies like cavities or dirty textured surfaces. Therefore, the main aim of the present research was to develop a method capable of drilling-induced delamination measurement in fibrous polymeric composites based on the image differentiation principle. In an attempt to implement this principle, images of the undrilled com-posites were referenced/compared with the images of the drilled composites. The proposed delamination measurement method is tested through mechanical drilling experiments in glass fibre reinforced polymer (GFRP) composites and compared with conventional DIP-supported manual measurements. The experimental results show a good agreement between the delamination detected by the naked eye, the conventional and the proposed method. Although the proposed method slightly increases the drilling operation time, the comparative differ-entiating makes it a good solution to detect drilling-induced material deformations in textured and semi-specular surfaces. The proposed method can separate drilling-induced delamination from other non-drilling-induced material discontinuities or anomalies. Considering the automated, reproducible and complex nature of the novel method, it may replace current qualification operations in high-end industries.

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