Fourier phase analysis combined with a fusion scheme in long pulse thermography

Fourier phase analysis (FPA) is a common routine in long pulse thermography (LPT). However, the change of appearance in maximum phase difference in the Fourier domain caused by different depths of defects results in low contrast images with fuzzy defect edges, limiting its application majorly. In this work, the detection capability of FPA is studied by modelling the image sequence length as a function of the defect depth, thereby quantifying the expected image sequence length for inspecting the defects at a specific depth and then, a strategy for selecting the optimal image sequence length is proposed by establishing the relationship between the maximum phase difference and the image sequence length. Followed by an image fusion procedure, the phase difference map with high-contrast defect edges can be obtained from the optimal image sequence. In addition, we show that the precooling treatment before detection is an effective way to improve the image quality for LPT. Experiments have been conducted in identifying defects in a typical glass fiber reinforced polymer (GFPR) with size of 200 × 150 × 6 mm3, where continuous thermal excitation for 100 s was provided by a pair of 1 kW halogen lamps and the images were recorded by an infrared camera with wavelength band of 8–14 μm. The resulting phase difference maps clearly present the edges of all defects with a signal-to-noise ratio greater than 43 dB, demonstrating the effectiveness of the proposed method in improving the image quality in LPT.