Effect of Background Subtraction on Defect Detection in Thermographic Signal Reconstruction Coefficient Images

When halogen lamps are used as the excitation source in long pulse thermography (LPT) of composite materials, the non-uniform surface temperature distribution will appear in the thermographic image recorded by the infrared camera and so the performance of the LPT technology will be affected severely. To address this issue, a simple method is proposed in this work to enhance the defect detectability for the LPT technique. In this method, the locations of the pixels in the non-defective area are firstly determined by an empirical rule, and then the thermal data of these non-defective areas is selected for estimating the non-uniform surface temperature distribution by a second order polynomial curve-fitting model. Finally, the thermal image sequences after non-uniform background removal are analyzed using thermographic signal reconstruction coefficients to enhance the quality of thermal images for damage detection further. To assess the performance of the method proposed in this paper, the defect detection experiment for the carbon fiber reinforced plastic (CFRP) using this method is carried out. Experimental results show that this method proposed in this paper can effectively remove the temperature non-uniformity, and it can reveal 11 out of 12 defects on the CFRP sample with a high signal-to-noise ratio of 9.09, where all the defects with aspect ratio >= 2.5 can be detected, and 1 illegible defect with aspect ratio of 1.67 can also be detected.

Automated summary

A simple and effective method is proposed in this paper to enhance the reliability of defect detection in composite materials by eliminating non-uniform surface temperature distribution and using thermographic signal reconstruction coefficients. Experimental results show that this method performs well in detecting defects on CFRP samples.