Study on intelligent recognition detection technology of debond defects for ceramic matrix composites based on terahertz time domain spectroscopy.

With the wide use of high-temperature-resistant ceramic matrix composites (CMCs) in aviation and space flight, it is important to detect the quality of the bonding. This paper used terahertz (THz) time-domain spectroscopy nondestructive testing technology to inspect the bonding defects of the CMC. This paper puts forward a method-extraction method, which is applied to make samples to simulate the bonding defect of CMC by embedding polytetrafluoroethylene (PTFE) sheets with 0.12 mm thickness into the adhesive layer and extracting it after curing and presetting the bonding defects. On the basis of the classical and analytical algorithms, such as the maximum in time-domain and power spectrum integration, through further study in the THz spectral characteristics of bonding samples for CMC, we specifically introduce the upper debond coefficient, lower debond coefficient, average absorption coefficient for the frequency domain, centroid coefficient for the frequency domain, and other characteristics. By optimizing the THz detection characteristics set, as a sample, we adopt the neural network intelligent recognition algorithm to detect the upper and lower debond defects in samples and realize the intelligent identification for CMC debond defects.