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.

中文翻译：

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UT控制辅助CFRP元件热处理工艺对比分析

目前的工作使用文献中最常见的算法恢复热数据处理，并另外引入了不同的数据处理策略，旨在改进工业复合材料的次表面缺陷检测。这些材料可以通过红外无损检测成功控制，因为可以通过热脉冲下的温度响应轻松检测到缺陷，并获得可靠的结果。为了减少无损检测的应用限制，拟议的研究表明可以将脉冲热成像技术与在 Matlab 环境中实施的准确图像处理方法相结合，以可靠、快速地表征地下和内部损伤。对所提议的研究案例，如完善的 DAC、PCT、TSR 程序，对热处理方法进行了评估。此外，作者提出了一种更好的缺陷表征，通过精细的数据处理和准确的实验程序实现，提供了可以轻松区分缺陷的详细对比图。这种改进的算法实现了缺陷映射的自动化，提高了缺陷检测的准确性，优化了根据整个热框架每个计算点相邻位置的空间变化识别缺陷边界。热数据采用标准方法评估，局部边界法用于具有人工缺陷的碳纤维复合材料试样，评估采用谷本准则的不同方法获得的处理图像。发现所提出的热计算方法适用于缺陷分布的自动映射，并针对被检测结构中的 Tanimoto 准则同时检测缺陷边界进行了优化。此外，还进行了超声波控制，用于不同控制程序之间的检测比较。