Enhancing fault characterisation in composites using infrared thermography: a bee colony optimisation approach with self-organising maps

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dc.contributor.authorPereira Barella, Bruno
dc.contributor.authorGarcia Rosa, Renan
dc.contributor.authorBarbosa de Oliveira, Gina Maira
dc.contributor.authorFernandes, Henrique
dc.date.accessioned2024-12-20T16:38:35Z
dc.date.available2024-12-20T16:38:35Z
dc.date.freetoread2024-12-20
dc.date.issued2024
dc.date.pubOnline2024-11-26
dc.description.abstractThis work presents an innovative approach aimed at enhancing the characterisation of discontinuities through the processing of thermographic images. The proposed methodology combines self-organising maps (SOM) with bio-inspired parameter optimisation through bee colony optimisation technique. The primary focus is on improving the quality of the fault quantification metric known as the signal-to-noise ratio (SNR). The goal is to achieve a better fault visualisation, ultimately contributing to the advance of thermography as a non-destructive technique. To validate this novel approach, an experiment was conducted using pulsed thermography on a unidirectional carbon laminate piece measuring 33 ✕100 mm. This specimen was intentionally equipped with three artificial delaminations positioned at different depths on specific layers. The results were then compared against conventional approaches such as principal component analysis, partial least-squares regression and polynomial approximation. The findings from this experiment demonstrated the potential of the proposed approach, i.e. the bee colony optimisation coupled with SOM, on the characterisation of discontinuities using infrared thermography data. There was a 15% improvement on the SNR when using the proposed approach over the other tested approaches. This research makes a noteworthy contribution by offering a promising technique for both the detection and characterisation of faults in composite materials.
dc.description.journalNameQuantitative InfraRed Thermography Journal
dc.description.sponsorshipCoordenação de Aperfeicoamento de Pessoal de Nível Superior, National Council for Scientific and Technological Development
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico [407140/2021-2]; Conselho Nacional de Desenvolvimento Científico e Tecnológico [312530/2023-4]; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior [001].
dc.identifier.citationPereira Barella B, Garcia Rosa R, Barbosa de Oliveira GM, Fernandes H. (2024) Enhancing fault characterisation in composites using infrared thermography: a bee colony optimisation approach with self-organising maps. Quantitative InfraRed Thermography Journal, Available online 26 November 2024, Article number 2432079
dc.identifier.eissn2116-7176
dc.identifier.elementsID560108
dc.identifier.issn1768-6733
dc.identifier.paperNo2432079
dc.identifier.urihttps://doi.org/10.1080/17686733.2024.2432079
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23303
dc.languageEnglish
dc.language.isoen
dc.publisherTaylor and Francis
dc.publisher.urihttps://www.tandfonline.com/doi/full/10.1080/17686733.2024.2432079
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectInfrared thermography
dc.subjectnon-destructive testing
dc.subjectcomposite materials
dc.subjectbee colony optimisation
dc.subjectself-organising maps
dc.subject46 Information and Computing Sciences
dc.subject40 Engineering
dc.subject4602 Artificial Intelligence
dc.titleEnhancing fault characterisation in composites using infrared thermography: a bee colony optimisation approach with self-organising maps
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.dateAccepted2024-11-04

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