Loading...
Detection of release fabric defects in fiber-reinforced composites using through-transmission ultrasound
LeMay, Gary S. Boldsaikhan, Enkhsaikhan
LeMay, Gary S.
Boldsaikhan, Enkhsaikhan
Citations
Altmetric:
Other Names
Location
Time Period
Advisors
Original Date
Digitization Date
Issue Date
2025-03-14
Type
Article
Genre
Keywords
Acoustic impedance,Confusion matrix,Fiber-reinforced composite,Nondestructive inspection,Release fabric,Through-transmission ultrasound
Subjects (LCSH)
Citation
LeMay, G., & Boldsaikhan, E. (2025). Detection of Release Fabric Defects in Fiber-Reinforced Composites Using Through-Transmission Ultrasound. Journal of Manufacturing and Materials Processing, 9(3), 94. https://doi.org/10.3390/jmmp9030094
Abstract
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. © 2025 by the authors.
Table of Contents
Description
This is an open access article under the CC BY license.
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Journal
Journal of Manufacturing and Materials Processing
Book Title
Series
Digital Collection
Finding Aid URL
Use and Reproduction
Archival Collection
PubMed ID
ISSN
25044494