Abstract
A novel algorithm for pixel-based thermal sequences processing based on R2 (coefficient of determination, COD) fractile threshold of non-linear fitting is proposed. Original data are obtained from active laser infrared thermography inspection to an aviation CFRP laminate with artificial defects. By fitting temperature sequence of pixels in a thermogram using the 1st-order and 2nd-order Fourier function, R2 is calculated and attached to each pixel. It is found that R2 of defective pixels is greater than that of non-defective pixels. The threshold for filtering background pixels is determined by histogram analysis of R2 set in a thermogram. Then fractile thresholds of R2 set separate pixels from defect and non-defect region. The temperature value of non-defect pixels is reduced to contrast with defect pixels. The edge of defects is sharpened, and detectable defects increase. Combining the fractile thresholds of 1st-order and 2nd-order Fourier fitting, the final processed thermograms exhibit improved detection performance evaluated by simplified probability of detection (POD) analysis and signal-to-noise ratio (SNR) calculation. In this work, the tested data show huge promotion of defect detection rate. Defect with an aspect ratio of 3.0 is detected. The combine-processed thermogram possess the maximum SNR of defective area.
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