Detection of Release Fabric Defects in Fiber-Reinforced Composites Using Through-Transmission Ultrasound

The detection of foreign material residues in fiber-reinforced composites (FRCs) is crucial, as such residues weaken the structural performance, especially when the acoustic impedance of the foreign material closely matches that of the composite material. To date, no methodology has been developed to improve the detection of such defects with similar acoustic impedance in the received signal without using echo-mode techniques. Release fabric was chosen because it is used in the fabrication of FRCs as a consumable, which must be removed after curing. An accidental residue of release fabric presents a significant challenge in detecting it within FRC laminates using through-transmission ultrasound (TTU) since its acoustic properties closely resemble the surrounding composite material, resulting in minimal impact on the transmitted signal and preventing accurate defect detection due to the lack of time-of-flight measurements. This paper leverages a novel threshold classifier to improve the detection of release fabric with through-transmission ultrasound (TTU), an inspection technique that operates without echo mode. Ultimately, this novel threshold classifier improves TTU inspection by offering greater sensitivity and detectability compared to conventional attenuation-based methods, particularly in the absence of echo mode and time-of-flight measurements. Future research will aim to investigate additional physical factors and deep learning approaches to further advance the TTU inspection method.