The influence of defect thickness on defect characterization using pulsed thermography: a numerical study on stainless steel material

Abstract The combined effect of defect thickness and lateral size on defect characterization in AISI 316 L Stainless Steel material using Pulsed Thermography method is studied numerically. As the defect volume (thickness and lateral width) decreases for the same depth, the magnitude of change in surface temperature decreases, deteriorating the defect visibility. The change in the surface temperature can be related to the apparent reduction in the Reflection Coefficient, R , of the material and defect interface. The finite difference analysis is used to simulate the Pulsed Thermography experiment on steel material. A least-square-based optimization technique is used to estimate the R as a function of defect depth and lateral size to establish a relationship between them. The contrast derivative and log 2nd derivative methods are used for depth quantification. To carry out the defect visibility study, a noise matrix was generated using noise data obtained from an actual IR camera and superimposed on the numerical results to create a dataset that closely resembles actual experimental data. The study concluded that the defect thickness has the least effect on defect visibility and depth quantification if the thickness of the defect is greater than 500 μm for Stainless Steel. This work provides useful insight into the impact of defect volume on the precise measurement of defect depth and its visibility.