A Time Frequency-Based Approach for Defect Detection in Composites Using Nonstationary Thermal Wave Imaging

Characterization of various industrial components without impairing their future utility increases the necessity of nondestructive testing (NDT) techniques. In recent years, active thermography catches the researcher’s interest due to its distinct abilities like whole-field, contact-free, economic, defended, noninvasive, and nondestructive type of investigation. High energy deposition at low frequencies accompanied with enhanced depth resolution requirements of active thermography grabs the interest of quadratic frequency-modulated (QFM) stimulus in the recent past. On the other hand, enhanced defect detection is dependent on the extraction of an appropriate time-frequency component of chirped thermal response through a suitable processing technique. The present work employs velocity synchronous linear chirplet transformation (VSLCT) to precisely map the nonlinear chirp rate of the extracted quadratic frequency modulated thermal response. The proposed methodology is validated by carrying experimentation over carbon fiber and glass fiber reinforced polymer samples with artificially made flat bottom holes and Teflon inserts. Defect detectability of the proposed technique is quantified by comparing conventional techniques with the figure of merit (FoM) as signal to noise ratio (SNR), full width at half maxima (FWHM), and probability of detection (POD). An arduous manual inspection of processed data recommends automatic defect detection through segmentation without manual intervention. An active contour-based segmentation is performed post to VSLCT technique to facilitate the automatic visualization of defects.