Open AccessDefect characterisation using pulse compression‐based quadratic frequency modulated thermal wave imaging
Author(s) -
Subhani Shaik,
Chandra Sekhar Yadav Gampa V.P.,
Ghali Venkata Subbarao
Publication year - 2020
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2019.0118
Subject(s) - reflection (computer programming) , materials science , acoustics , pulse compression , ranging , optics , scattering , pulse (music) , signal processing , geology , electronic engineering , computer science , detector , engineering , physics , telecommunications , radar , geodesy , digital signal processing , programming language
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.