Article Article
Foreign Object Identification within a Laminated Carbon Fiber Composite Using Pulse-Echo Ultrasonics

Carbon fiber composites are becoming increasingly popular in a wide variety of industries including aerospace, automotive, and athletics. During manufacturing, foreign objects such as loose peel ply, bagging materials, etc. may embed themselves between laminae causing localized weaknesses, crack initiators, and stress risers. This has created a need to characterize these composite parts and identify these defects in a nondestructive manner. This research improves upon existing technologies for identifying foreign objects within carbon fiber composites. To simulate embedded foreign objects within a composite structure, Polytetraflouride (PTFE) inclusions were placed between laminae during manufacturing to simulate a manufacturing induced foreign object. The embedded inclusions measure 0.002 in. (0.05 mm) in thickness. Making use of a custom in‐house ultrasonic immersion scanner, several techniques are presented in this work to identify PTFE inclusions based off of the resulting c‐scan data using custom MATLAB code. Results show that circular inclusions with a radius as small as 0.07 in. (1.9 mm) in can be identified, with the highest contrast for identification coming from the presented spatial averaging technique. In addition, the location of the object within the laminate stack can be determined, and results are presented for a 10 lamina composite with a successful identification of foreign objects throughout the entire part.

  • Sloan, J, 2016, “Composites 101: Fibers and resin.” from
  • Hassan, M.H., Othman, A.R. and Kamaruddin S., 2017, “A review on the manufacturing defects of complex-shaped laminate in aircraft composite structures,” The International Journal of Advanced Manufacturing Technology, 91(9-12), pp. 4081-4094.
  • Kaddour, A. and Hinton, M., 2013, “Maturity of 3D failure criteria for fibre-reinforced composites: Comparison between theories and experiments: Part B of WWFE-II,” Journal Of Composite Materials, 47(6-7), pp 925-966.
  • Kaddour, A., Hinton, M., Smith, P. and Li S., 2013, “The background to the third world-wide failure exercise,” Journal of Composite Materials, 47(20-21) pp. 2417-2426.
  • Duchene, P., Chaki, S., Ayadi, A. and Krawczak P., 2018, “A review of non-destructive techniques used for mechanical damage assessment in polymer composites,” Journal of Materials Science, 53(11), pp 7915-7938.
  • L. W. Schmerr Jr, Fundamentals of Ultrasonic Nondestructive Evaluation: A Modeling Approach, 1998 edition. New York: Springer, 1998.Yolken, H.T. and Matzkanin, G.A., 2009, “Nondestructive Evaluation of Advanced Fiber Reinforced Polymer Matrix Composites: A Technology Assessment,” NASA/CR-2009-215566, National Aeronautics and Space Administration, Hanover, Maryland.
  • Poudel, A., Kanneganti, R., Li, S., Gupta, L., and Chu, T., 2015, “Classification of ultrasonic echo signals to detect embedded defects in carbon fibre reinforced plastic laminates,” International Journal of Microstructure and Materials Properties, 10(3-4), pp. 216-230.
  • N. Takeda and S. Minakuchi, “Optical fiber sensor based life cycling monitoring and quality assessment of carbon fiber reinforced polymer matrix composite structures,” in 2017 25th Optical Fiber Sensors Conference (OFS), 2017, pp. 1–4.
  • T. Barry, M. Kesharaju, C. Nagarajah, and S. Palanisamy, “Defect characterisation in laminar composite structures using ultrasonic techniques and artificial neural networks,” J. Compos. Mater., vol. 50, no. 7, pp. 861–871, Mar. 2016.
Usage Shares
Total Views
99 Page Views
Total Shares
0 Tweets
0 PDF Downloads
0 Facebook Shares
Total Usage