The effect of defect size on the quantitative estimation of defect depth using sonic infrared imaging

Abstract

Sonic infrared (SIR) imaging is a hybrid nondestructive evaluation (NDE) method that uses ultrasonic excitation along with thermal imaging to detect defects in materials and structures. SIR NDE uses an ultrasonic pulse in the 15–40 kHz range from a transducer to produce localized heating at the defect while a thermal camera will record surface temperature during the inspection. In a previous article, we presented a model that describes heat diffusion from subsurface defects in a composite material. The model uses certain aspects of the temperature-time curve for defect depth profiling, namely, half-maximum power time, the peak slope time, and the second derivative peak time. In this study, we investigate the effect of defect size on the quantitative estimation of defect depth. The theoretical results are calculated and compared with the experimental data. We demonstrate that the experimental data have good correlation with the theoretical calculation. The peak slope time and the second derivative peak time are less sensitive to changes in defect size than the half-maximum power time in the defect depth assessment.