Infrared non-destructive testing and evaluation is one of the promising inspection methods for characterization of wide verity of materials due to its merits and applicability to test materials irrespective of their electrical, mechanical, acoustical and magnetic properties. Among the various infrared non-destructive evaluation modalities such as pulse based thermography and mono frequency excited modulated lock-in thermography, recently proposed matched filter based non-periodic infrared thermographic approaches gained their importance due to their superior sub-surface defect detection in terms of resolution and sensitivity. The present work demonstrates the merits of frequency modulated thermal wave imaging for identification of concrete in concrete structure. Obtained results shows the matched filter based post-processing schemes exhibits better depth scanning capabilities compared with the conventional frequency domain phase approach to detect corrosion in the concrete structures.
Non-destructive testing and evaluation methods demand various efficient post processing approaches to enhance their defect detection capabilities of the adopted technique. Among them, widely used statistical methods are Eigen domain based post processing approach such as principal component analysis and recently proposed correlation based pulse compression approach. In this work, experiments have been carried out to highlight the capabilities of these data processing schemes for detection of subsurface defects in fibre reinforced polymer test samples. Obtained results clearly show that the defect detection capability of the correlation (matched filter) based post processing approach is far superior than that of the principal component analysis based data processing approach. Further, the similarities and differences between these proposed methods have been highlighted.
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