The Inspection of CFRP Laminate with Subsurface Defects by Laser Arrays Scanning Thermography (LAsST)

Laser array scanning thermography (LAsST) was used to detect the subsurface defects of carbon fiber reinforced composite (CFRP). A series of bottom flat hole (BFHs) of CFRP were prepared for LAsST. Truncation pseudo-static matrix reconstruction (TC-PSMR) method was used to reconstruct the thermal response signal. Fast Fourier transform (FFT), principal component analysis (PCA) and partial least squares regression (PLSR) were used to process the thermal response signals, forming FFT image, PCA image, and PLSR image. The signal noise ratios (SNRs) of defects is calculated, and it is used to evaluate the defect detection ability of different post-processing algorithms. The experimental results show that the image based on FFT phase has a higher signal-to-noise ratio with PLSR image, and the FFT amplitude image and PLSR image can accurately represent the defect size.