DMD-T: Thermographic Inspection of Composites using Dynamic Mode Decomposition

Liangliang Cheng, Yunpeng Zhu, Mathias Kersemans

OnderzoeksoutputAcademic

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Samenvatting

In the realm of Non-Destructive Testing (NDT) of fibre reinforced polymers, InfraRed Thermography (IRT) serves as a valuable tool for diagnosis. Various processing techniques, such as principal component analysis, Fourier transformation, and thermographic signal reconstruction, are commonly utilized to improve the identification of defects. However, the practical application of infrared thermography is limited by the need for expert operator experience, which hampers its broader adoption in industrial settings. This paper presents a preliminary examination of the application of data-driven based Dynamic Mode Decomposition (DMD) to study the thermal dynamics of composites and evaluate its potential for defect detection. The new method is known as the DMD for Thermography (DMD-T). The performance has been validated via an experimental dataset of a Carbon Fibre Reinforced Polymer (CFRP) plate with an impact damage.
Originele taal-2English
Titel5th International Conference on Industrial Artificial Intelligence (IAI)
UitgeverijIEEE Xplore
Aantal pagina's4
ISBN van elektronische versie979-8-3503-2529-4
ISBN van geprinte versie979-8-3503-2530-0
DOI's
StatusPublished - 21-aug.-2023
Evenement2023 5th International Conference on Industrial Artificial Intelligence (IAI) - Xi'an, China, Xi'an, China
Duur: 21-aug.-202324-aug.-2023

Conference

Conference2023 5th International Conference on Industrial Artificial Intelligence (IAI)
Land/RegioChina
StadXi'an
Periode21/08/202324/08/2023

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