Defect characterisation using pulse compression-based quadratic frequency modulated thermal wave imaging

Abstract

Quantitative depth estimation, along with enhanced defect detectability, is of utmost importance for subsurface analysis in thermal wave imaging for a variety of applications. However, the size and the depth of the subsurface anomalies influence this quantitative analysis due to the non-consideration of back reflection from the defect boundary in addition to three-dimensional scattering effects. This study explores an experimental validation of an analytical model for quantitative depth analysis of subsurface anomalies in thermal wave detection and ranging using quadratic frequency-modulated stimulation with pulse compression based signal processing approach and presents the depth resolution feature by considering the back reflection at the defect boundary. It also presents a study on the influence of the size of the anomaly and bandwidth of the stimulation on quantitative depth prediction using the experimentation carried over a carbon fibre reinforced plastic and mild steel specimen with artificial flat-bottom holes.