In the field of thermal non-destructive testing and evaluation (NDT&E), active thermography has gained significant popularity due to its ability to enable rapid, remote and wide-area inspection without compromising the structural integrity of materials. Among various active thermographic techniques, digitised frequency-modulated thermal wave imaging (DFMTWI), a pulse compression favourable excitation technique, offers notable advantages in terms of depth resolution and defect detectability. This study presents a proof-of-concept experimental investigation on a hardened steel specimen commonly used in shipbuilding, incorporating a flat-bottomed hole defect. The specimen was thermally excited using a digitised frequency-modulated heat flux. To assess defect detection performance, three distinct statistical post-processing approaches were applied: the frequency-domain phase (FDP), the time-domain phase (TDP) and cross-correlation coefficient (CCC) analysis. Their effectiveness was quantitatively evaluated using the signal-to-noise ratio (SNR) as the primary figure of merit. Experimental results show that the CCC yields superior performance, significantly outperforming the TDP and FDP. The findings highlight the enhanced sensitivity and robustness of correlation-based analysis in detecting subsurface anomalies under DFMTWI excitation. This work underscores the potential of advanced signal processing in improving the applicability of thermal wave imaging for high-resolution, non-invasive material inspection.
Singh et al. (Thu,) studied this question.