Comparative Analysis of Thermal Processing Approaches for a CFRP Element Aided by UT Control

The present work resumes thermal data processing with most common algorithms in literature and introduces in addition a different data processing strategy, proposed to improve subsurface defect detection on industrial composites. These materials are successfully controlled with infrared Non-Destructive Investigations, since defects are easily detected by temperature response under thermal pulses with reliable results. To reduce application limits for non-destructive inspections, the proposed research shows possibility to combine pulsed thermographic technique with accurate image-processing methods implemented in Matlab environment for a reliable and rapid characterization of subsurface and internal damage. Thermal processing methods are evaluated for the proposed case of study, as the well-established DAC, PCT, TSR procedures. In addition, the authors proposed a better defect characterization that is achieved with refined data processing and accurate experimental procedures, providing detailed contrast maps where defects are easily distinguished. This improved algorithm automates the defect mapping and enhances the accuracy of defects inspection, optimized to identify defect boundaries according to spatial variations in neighboring of each calculation point of the whole thermal frame. Thermal data are evaluated with standard methods and the local boundary method is for carbon-fiber composite specimens with artificial defects, evaluating processed images obtained by different methods employing the Tanimoto criterion. Proposed thermal computation method is found suitable for automatic mapping of defect distribution and optimized for simultaneous defect boundaries’ detection in terms of Tanimoto criterion, in the inspected structure. In addition, ultrasonic controls are carried out for detection comparison between different control procedures.