Abstract

Carbon fiber reinforced plastic (CFRP) materials are widely used in aircraft and wind turbine blades due to their low weight and high strength. Surface cracks, impact damages, and delaminations are the most common defects for CFRP composites. In this paper, the principal component analysis (PCA)-based eddy-current pulsed thermography method is proposed to detect and visualize defects from transient thermal images or videos. More specifically, three types of defects are classified based on their transient temperature behaviors using PCA at the pixel levels and optical flow patterns at the image levels. In addition, through feature extraction from optical flow method, the quantitative information about the defects, such as a defective area, is retrieved at the image levels.

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