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22 April 2009 Enhanced contrast detection of subsurface defects by pulsed infrared thermography based on the fourth order statistic moment, kurtosis
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Abstract
The automatic detection of subsurface defects has become a desired goal in the application of non-destructive testing and evaluation techniques. In this paper, an algorithm based on the fourth order standardised statistic moment, i.e. kurtosis, is proposed for detection and/or characterization of subsurface defects having a thermal diffusivity either higher or lower than the host material. The analysis of thermographic data for the detection of defects can be reduced to the temporal statistics of the thermographic sequence. The final result provided by this algorithm is an image showing the different defects without the necessity of establishing other evaluating parameters such as the delayed time of the first image or the acquisition frequency in the analysis, which are required in other processing techniques. All the information is contained in a single image allowing to discriminate between the defect types (high o low thermal diffusivity). Synthetic data from Thermocalc® and experimental works using a PlexiglasTM specimen were performed showing good agreement. Processed results using synthetic and experimental data with other methods used in the field of thermography for defect detection and/or characterization are provided as well for comparison.
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Francisco J. Madruga, Clemente Ibarra-Castanedo, Olga M. Conde, Xavier P. Maldague, and José M. López-Higuera "Enhanced contrast detection of subsurface defects by pulsed infrared thermography based on the fourth order statistic moment, kurtosis", Proc. SPIE 7299, Thermosense XXXI, 72990U (22 April 2009); https://doi.org/10.1117/12.818684
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