Abstract
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.
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Acknowledgements
This work was supported by the Foundation for Innovative Research Groups of the National Nature Science Foundation of China under Grant No. 51521003, National Natural Science Foundation of China under Contract Nos. 61571153, 51173034, Self-planned Task of State Key Laboratory of Robotics and System (HIT), and the Programme of Introducing Talents of Discipline of Universities (Grant No. B07108) for the research support.
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Wei, J., Wang, F., Liu, J. et al. The Inspection of CFRP Laminate with Subsurface Defects by Laser Arrays Scanning Thermography (LAsST). Int J Thermophys 41, 60 (2020). https://doi.org/10.1007/s10765-020-02639-2
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DOI: https://doi.org/10.1007/s10765-020-02639-2