Active infrared imaging for estimation of Sub-Surface features in a steel material

Abstract

Non-destructive Testing (NDT) using infrared thermography plays a crucial role in detecting sub-surface defects in various components/materials. Post-processing of the acquired thermographic data is essential to extract significant information.In this paper, simulated data for infrared thermography of carbon steel has been considered. The steel sample is modeled and simulated with six different defects having different properties. The simulated data is processed with Principal Component Analysis (PCA). Further the thermal data is reconstructed by considering different principal components to ascertain their significance. The reconstructed image sequence from the second principal component provides sub-surface slag defects thermal characteristics with significant Signal to Noise Ratio (SNR) value in comparison with the other principal components.