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Damage Sensitivity and Multiple Damage Detection in Glass Fiber/Epoxy Laminates With Carbon Black Filler via Electrical Impedance Tomography

[+] Author Affiliations
T. N. Tallman, K. W. Wang

University of Michigan, Ann Arbor, MI

Paper No. SMASIS2014-7403, pp. V001T05A001; 6 pages
doi:10.1115/SMASIS2014-7403
From:
  • ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring; Keynote Presentation
  • Newport, Rhode Island, USA, September 8–10, 2014
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-4614-8
  • Copyright © 2014 by ASME

abstract

Utilizing conductivity changes to locate matrix damage in glass fiber reinforced polymers (GFRPs) manufactured with nanocomposite matrices is a promising avenue of composite structural health monitoring (SHM) with the potential to ensure unprecedented levels of safety. Nanocomposites depend on the formation of well-connected nanofiller networks for electrical conductivity. Therefore, matrix damage that severs the connection between nanofillers will manifest as a local change in conductivity. This research advances state of the art conductivity-based SHM by employing electrical impedance tomography (EIT) to locate damage-induced conductivity changes in a glass fiber/epoxy laminate manufactured with carbon black (CB) filler. EIT for damage detection is characterized by identifying the lower threshold of through-hole detection and demonstrating the capability of EIT to accurately resolve multiple through holes. It is found that through holes as small as 3.18 mm in diameter can be detected, and EIT can detect multiple through holes. However, sensitivity to new through holes is diminished in the presence of existing through holes unless a damaged baseline is used. These research findings demonstrate the considerable potential of conductivity-based health monitoring for GFRP laminates with conductive networks of nanoparticles in the matrix.

Copyright © 2014 by ASME

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