Optimization of Thermal-Wave Radar Thermography by Transverse Heat Flow Suppression Technique for Accurate Defect Detection of CFRP Laminates

In this study, transverse heat flow suppression (THFS) technique was proposed to enhance the ability of thermal-wave radar thermography (TWRT) to resist lateral thermal diffusion and uneven heating. The enhanced TWRT was used to detect subsurface defects of carbon fiber reinforced plastic (CFRP) laminates. The principle of THFS was described in detail by the optical flow analogy. The three-dimension (3-D) thermal-wave model stimulated by the uneven linear frequency modulation (LFM) thermal flow was introduced. The thermal-wave signal was processed by several different postprocessing characteristic extraction algorithms [Cross-correlation algorithm (CC), dual-orthogonal demodulation algorithm (DOD), fractional Fourier transform (FrFT), and principal component analysis (PCA)]. The comparison between normalized DOD amplitude/phase and normalized DOD-THFS amplitude/phase was carried out. The simulation results depicted THFS can significantly improve the difference between defect location and nondefect location. Nine CFRP specimens with artificial flat-bottom holes (FBHs) were prepared for nondestructive testing and evaluation (NDTE) by enhanced TWRT. Seventy-two FBHs were prepared to test the probability of detection (PoD) of the enhanced TWRT. Hit/miss method was used to count defect information. The results demonstrated that the enhanced TWRT can realize the effective detection of defects (90% detection probability) with a diameter depth ratio of 5.06 under 95% confidence level. Compared with two state-of-the-art approaches, the proposed DOD-THFS phase has a better defect detection signal-to-noise ratio (SNR).