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.
Infrared non-destructive testing and evaluation is one of the most promising inspection methods for evaluating variety of materials due to its merits such as remote based, whole field, safe and quantitative inspection capabilities. Among the various infrared non-destructive evaluation methods, pulse based thermography and mono frequency excited modulated lock-in thermography gained importance due to their simple experimentation procedure and data processing approaches involved. However, recently proposed matched filter based non-periodic infrared thermographic approaches gained importance due to their superior sub-surface defect identification capabilities in terms of detection resolution and sensitivity. The present work demonstrates the merits of pulse compression favorable thermal wave imaging approach for identification of flat bottom holes in a carbon fiber reinforced polymer material.
InfraRed Thermography (IRT) is one of the widely used Non-destructive Testing and Evaluation (NDT and E) method for characterization of fiber reinforced polymers. Among various testing methodologies and associated post processing schemes, recently proposed pulse compression favorable thermal wave imaging methodologies gained importance due to their enhanced test sensitivity and resolution for identifying the sub-surface defects. The present paper highlights a highly depth resolved pulse compression favorable thermal wave imaging methodology for identification of subsurface defects in a Glass Fiber Reinforced Polymer (GFRP) test specimen.
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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