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dc.contributor.authorRoemer, Jakub
dc.contributor.authorKhawaja, Hassan
dc.contributor.authorMoatamedi, Mojtaba
dc.contributor.authorPieczonka, Lukasz
dc.date.accessioned2023-03-29T11:32:08Z
dc.date.available2023-03-29T11:32:08Z
dc.date.issued2023-02-08
dc.description.abstractThis paper proposes a data processing scheme for laser spot thermography (LST) applied for nondestructive testing (NDT) of composite laminates. The LST involves recording multiple thermographic sequences, resulting in large amounts of data that have to be processed cumulatively to evaluate the diagnostic information. This paper demonstrates a new data processing scheme based on parameterization and machine learning. The approach allows to overcome some of the major difficulties in LST signal processing and deliver valuable diagnostic information. The effectiveness of the proposed approach is demonstrated on an experimental dataset acquired for a laminated composite sample with multiple simulated delaminations. The paper discusses the theoretical aspects of the proposed signal processing and inference algorithms as well as the experimental arrangements necessary to collect the input data.en_US
dc.identifier.citationRoemer J, Khawaja HA, Moatamedi M, Pieczonka. Data Processing Scheme for Laser Spot Thermography Applied for Nondestructive Testing of Composite Laminates. Journal of nondestructive evaluation. 2023;42en_US
dc.identifier.cristinIDFRIDAID 2124703
dc.identifier.doihttps://doi.org/10.1007/s10921-023-00932-2
dc.identifier.issn0195-9298
dc.identifier.issn1573-4862
dc.identifier.urihttps://hdl.handle.net/10037/28884
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.relation.journalJournal of nondestructive evaluation
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2023 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleData Processing Scheme for Laser Spot Thermography Applied for Nondestructive Testing of Composite Laminatesen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)