Abstract:
Infrared thermographic techniques show their
potential usage for non-destructive testing and evaluation of
various materials due to their inherent capabilities such as
whole field, non-contact, qualitative and quantitative to detect
surface and sub-surface anomalies. This contribution intro-
duces a novel data analysis scheme by spectral reshaping of
linear frequency modulated temperature profile captured over
a mild steel specimen. Time and frequency domain based
processing methods are adopted on the generated temporal
thermal data to reveal the hidden defects. Obtained results
show the potential capabilities of spectral reshaping based
on Gaussian windowed chirp with enhanced resolution and
sensitivity for sub-surface defect detection.
