TY - JOUR
TI - Defect detection of GFRP/Nomex honeycomb sandwich structure by linear frequency modulation infrared thermal imaging
AU - Tang Qing-Ju
AU - Fan Wei-Ming
AU - Ji Juan
AU - Song Ya-Fei
JN - Thermal Science
PY - 2021
VL - 25
IS - 6
SP - 4611
EP - 4619
PT - Article
AB - Honeycomb sandwich material is a new material widely used in many fields, but  it is easy to produce defects such as delamination and ponding in the  process of manufacturing and service. First, a honeycomb sandwich sample  containing delamination defects and water accumulation was built. Then, a  linear frequency modulated driving halogen lamp is used as the excitation  source. Finally, the surface thermal image sequence of the test sample is  acquired by infrared thermal imager. Image sequences are processed by  inter-frame difference-multi-frame cumulative average method, principal  component analysis, Fourier transform method, and logarithmic polynomial  fitting method, respectively. Define and calculate the signal-to-noise ratio  of the heat map processed by each algorithm. Compared with the other three  algorithms, the principal component analysis method processed the image with  the highest signal-to-noise ratio and high contrast. This algorithm achieves  effective identification of delamination defects and water accumulation in  GFRP/Nomex honeycomb sandwich structure.