Toward automated identification and quantification of meso-scale damage modes in plain weave glass/epoxy composite laminates

Abstract

We investigated three different automated methods for identification and quantification of meso-scale damage on single-layer composite laminates subjected to ballistic impact by a 5.5 mm (0.22 caliber) right circular cylindrical steel projectile. These methods were based on the combined use of high-resolution optical imaging, fluorescence microscopy, and image detection software. High-resolution images of impacted composite samples were processed using either ImageJ alone (method 1, for sample size of 20 × 20 cm2) or ImageJ plus MATLAB (method 2, for sample size of 20 × 20 cm2), or fluorescence images were processed using ImageJ plus MATLAB (method 3, for sample size of 6 × 5 cm2). These methods were used for identification and grouping of horizontal and vertical transverse tow cracks, and 45° matrix cracks. The identified and grouped damage modes were quantified based on spatial pixel count related to damage modes, and quantified damage modes were used to generate a digital damage map using a separate MATLAB code for all three methods. Finally, the advantages and shortcomings of each of these three automated methods for identification and quantification of meso-scale damage modes were evaluated via comparison to a baseline manual method for identifying and quantifying the damage modes on the same samples.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 19, 2019
Source ID
10.1177/1056789519887215

Entities

People

  • Bazle Z. Haque
  • Bridgit Kioko
  • Christopher S. Meyer
  • Daniel J. O'brien
  • Enock Bonyi
  • Janelle Guy
  • John W. Gillespie Jr.
  • Kadir Aslan
  • Oreoluwa Adesina
  • Taofeek Obafemi-babatunde

Organizations

  • Morgan State University
  • United States Army Research Laboratory
  • University of Delaware

Tags

Readers

  • Image Processing and Computer Vision.
  • Regression Analysis.
  • Reinforced Composite Materials