Research on the quantitative analysis of subsurface defects for non-destructive testing by lock-in thermography

This paper describes the quantitative analysis of the boundary, location and depth of subsurface defects by lock-in thermography. The phase difference between defective areas and non-defective areas illustrates the qualitative analysis of the boundary and the location of the subsurface defect. In order to accurately estimate the size, location and depth of the defects, the phase is normalised, the heat transfer partial differential equation (PDE) model is used to filter the noise of normalised phase image and the differential normalised phase profile is employed to determine the boundary and location of the defect. The profile of the differential normalised phase distribution has maximum, minimum and zero points that help to quantitatively determine the boundary and location of the subsurface defect. An artificial neural network (ANN) is proposed to determine the depth of the subsurface defect. Experimental results for a steel plate, a carbon fibre-reinforced polymer (CFRP) sheet–foam sandwich, and honeycomb structure composites with artificial subsurface defects show good agreement with the actual values.

► Quantitative non-destructive evaluation (QNDE) of defects plays an important role in NDT.
► Heat transfer partial differential equation (PDE) is used to improve the contrast of the image.
► Size and location of the defect is determined by taking a derivative of normalised phase profile.
► An artificial neural network (ANN) is proposed to determine the depth of the subsurface defect.
► Experimental results show good agreement with actual values.