Abstract
Electromagnetic inductive thermography has performed well in the field of non-destructive testing (NDT) in recent years. In this study, a moving mode of induction thermography is used to study the temperature distribution near the defects with distinct spacing. The temperature profiles among different holes are analyzed within 100 mm/s, and the equivalent heating model of scanning mode and the best detection speed are provided. The temperature distribution among different area is analyzed and the temperature-based feature decline trend is determined. A feature enhancement method, involving classical deblurring and edge detection, is used to extract defect information by suppressing background noise. Following this, both PSNR (Peak Signal to Noise Ratio) and Structural Similarity (SSIM) for each image sequence processing were compared.
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