Microcracks are a common metallic defect, resulting in degradation of material properties. In this paper, specimens with different fatigue microcracks were detected by eddy current pulsed thermography (ECPT). Signal processing algorithms were investigated to improve the detectability and sensitivity; principal component analysis (PCA) and Tucker decomposition were used to compare the performance of microcrack detection. It was found that both algorithms were highly adaptable. A thermal quotient was used to assess the temperature variation trend. Furthermore, the potential correspondence between crack closure and temperature change was investigated.

中文翻译：

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涡流脉冲热像仪检测疲劳微裂纹

微裂纹是常见的金属缺陷，会导致材料性能下降。在本文中，通过涡流脉冲热像仪（ECPT）检测了具有不同疲劳微裂纹的标本。研究了信号处理算法以提高可检测性和灵敏度；主成分分析（PCA）和塔克分解用于比较微裂纹检测的性能。发现这两种算法都具有高度的适应性。使用热商来评估温度变化趋势。此外，研究了裂纹闭合与温度变化之间的潜在对应关系。