66
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Characterization of drilling damage in glass laminate composites using lock-in thermography nondestructive evaluation method: a feasibility study

ORCID Icon, ORCID Icon & ORCID Icon
Pages 615-624 | Received 22 Jun 2022, Accepted 05 Oct 2022, Published online: 18 Oct 2022
 

ABSTRACT

The drilling of composite structure leads to its damage, near the peripheral areas of the drilled hole, due to the laminar structure of the composites. The goodness of a drilling process can be evaluated by measuring the extent of the damage caused by it. In the present study, lock-in thermography non-destructive inspection method is proposed to characterise the drilling damages in glass fiber–reinforced polymer panel. A semi-automated image processing methodology is proposed to calculate damage parameters, namely delamination area and size, and delamination factor. The effect of excitation frequency on the damage characterisation is studied to decide the optimum frequency range to measure the damage parameters through signal-to-noise ratio and damage visibility. The damage parameters are measured at optimum frequency. The study showed that the lock-in thermography technique has the potential to characterise drilling damage.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

Raw data were generated at the Center for Imaging Technologies, M S Ramaiah Institute of Technology. Derived data supporting the findings of this study are available from the corresponding author SD on request.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 199.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.