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3 May 2019 The influence of the truncation window size on the quantitative thermographic results after a pulsed test on an aluminium sample: comparison among different post-processing algorithms
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Abstract
Pulsed thermography is a commonly used infrared thermal technique for non-destructive evaluation of engineering materials and components. The quality of the obtained results, in terms of sizes and depths of the researched defects depends mostly on the data processing methods and the observed time intervals. This work is focused on the algorithms used for processing the thermal data after a pulsed test: Pulsed Phase Thermography (PPT), Principal Component Thermography (PCT), Thermographic Signal Reconstruction® (TSR®), Slope and R2. The work focuses on an aluminium sample with shallow imposed defects and regards the post-processing analysis with different algorithms by considering different lengths of the cooling sequence (time interval or number of frames) and the investigation of the correlation between the signal contrast and the aspect ratio of defects. This correlation represents a first attempt for estimating the size and the depth of the defects, with a new empirical approach. Results show as the influence of the truncation window size changes according to the algorithm used for data analysis and the depth and the size of the detected defects. Moreover, each algorithm has its own peculiarities and capabilities and a synergic action in defects detection and characterization can be obtained if more algorithms are applied on the same thermal sequence.
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ester D'Accardi, Davide Palumbo, Rosanna Tamborrino, and Umberto Galietti "The influence of the truncation window size on the quantitative thermographic results after a pulsed test on an aluminium sample: comparison among different post-processing algorithms", Proc. SPIE 11004, Thermosense: Thermal Infrared Applications XLI, 110040M (3 May 2019); https://doi.org/10.1117/12.2518984
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