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.
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