Automatic histogram-based defect detection in glass fibre reinforced polymer composites using terahertz time-domain spectroscopy reflection imaging

Abstract

We developed a method for automatic detection of defects in glass fibre reinforced polymer (GFRP) based on a terahertz time-domain spectroscopy (TDS) system. Two GFRP specimens with round defects of different sizes (inclusions and delaminations) were measured by means of a high-speed TDS reflective scanner with an electronically controlled optical sampling scheme. The algorithm provided a series of C-scans, which were then pre-selected to identify only those with features potentially associated with defects. A thresholding method based on Gaussian fitting of the histogram was developed. The results showed that 87 % of defects were detected for the specimen with inclusions and 100 % for the specimen with delaminations. The algorithm also provided information about the depth of defects, as each C-scan was assigned to a time slice. The results demonstrate that the TDS-based system, along with the proposed histogram-based method, can automatically detect defects in GFRP. © 2017 Elsevier Inc. All rights reserved.