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Quantifying uncertainty in pulsed thermographic inspection by analysing the thermal diffusivity measurements of metals and composites

Addepalli, S., Zhao, Y., Erkoyuncu, J. A. and Roy, R. ORCID: 0000-0001-5491-7437 (2021). Quantifying uncertainty in pulsed thermographic inspection by analysing the thermal diffusivity measurements of metals and composites. Sensors, 21(16), 5480. doi: 10.3390/s21165480


Pulsed thermography has been used significantly over the years to detect near and subsurface damage in both metals and composites. Where most of the research has been in either improving the detectability and/or its applicability to specific parts and scenarios, efforts to analyse and establish the level of uncertainty in the measurements have been very limited. This paper presents the analysis of multiple uncertainties associated with thermographic measurements under multiple scenarios such as the choice of post-processing algorithms; multiple flash power settings; and repeat tests on four materials, i.e., aluminium, steel, carbon-fibre reinforced plastics (CFRP) and glass-fibre reinforced plastics (GFRP). Thermal diffusivity measurement has been used as the parameter to determine the uncertainty associated with all the above categories. The results have been computed and represented in the form of a relative standard deviation (RSD) ratio in all cases, where the RSD is the ratio of standard deviation to the mean. The results clearly indicate that the thermal diffusivity measurements show a large RSD due to the post-processing algorithms in the case of steel and a large variability when it comes to assessing the GFRP laminates.

Publication Type: Article
Additional Information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords: thermal diffusivity; uncertainty quantification; pulsed thermography
Subjects: T Technology > TJ Mechanical engineering and machinery
Departments: School of Mathematics, Computer Science & Engineering
Date available in CRO: 02 Sep 2021 07:44
Date deposited: 2 September 2021
Date of acceptance: 11 August 2021
Date of first online publication: 14 August 2021
Text - Published Version
Available under License Creative Commons: Attribution International Public License 4.0.

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