Independent component thermography for non-destructive testing of defects in polymer composites

Abstract

Thermographic data processing and analysis is critical for effective infrared thermography non-destructive testing of defects in composite materials. In this research work, the concept of blind source separation is introduced into this field for facilitating subsurface defect detection in polymer composites. In detail, a thermal image generated by infrared thermography is viewed as a linear mixture of several independent and non-Gaussian sources, which can be decomposed by adopting the proposed independent component thermography (ICT) technique. After the decomposition, the non-Gaussian sources are extracted and plotted as a number of images with the same size as the original thermograms. Eventually, the defect signals can be separated from the non-uniform backgrounds which are usually caused by uneven heating. As a result, the location and shape information of the subsurface defective regions is highlighted. The feasibility of the ICT method is illustrated with its application to a carbon fiber reinforced polymer specimen.