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Independent component thermography for non-destructive testing of defects in polymer composites

机译:用于非破坏性测试的聚合物复合材料的无损性能热成像

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摘要

Thermographic data processing and analysis is critical for effective infrared thermography non-destructive testing of defects in composite materials. In this research work, the concept of blind source separation is introduced into this field for facilitating subsurface defect detection in polymer composites. In detail, a thermal image generated by infrared thermography is viewed as a linear mixture of several independent and non-Gaussian sources, which can be decomposed by adopting the proposed independent component thermography (ICT) technique. After the decomposition, the non-Gaussian sources are extracted and plotted as a number of images with the same size as the original thermograms. Eventually, the defect signals can be separated from the non-uniform backgrounds which are usually caused by uneven heating. As a result, the location and shape information of the subsurface defective regions is highlighted. The feasibility of the ICT method is illustrated with its application to a carbon fiber reinforced polymer specimen.
机译:热成像数据处理和分析对于复合材料中有效的红外热成像无损检测至关重要。在这项研究工作中,将盲源分离的概念引入了该领域,以便在聚合物复合材料中促进地下缺陷检测。详细地,通过红外热成像产生的热图像被视为几种独立和非高斯源的线性混合物,其可以通过采用所提出的独立分量热成像(ICT)技术来分解。在分解之后,将非高斯源提取并绘制为与原始热图相同的尺寸的数量图像。最终,缺陷信号可以与通常由不均匀加热引起的非均匀背景分离。结果,突出了地下缺陷区域的位置和形状信息。 ICT方法的可行性用其应用于碳纤维增强聚合物样本。

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