Damage detection via electrical impedance tomography in glass fiber/epoxy laminates with carbon black filler

Tyler N. Tallman, Sila Gungor, K. W. Wang, Charles E. Bakis

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

The conductivity of glass fiber reinforced polymers with nanocomposite matrices can be leveraged for structural health monitoring. Since nanocomposite matrices depend on well-connected networks of conductive nanofillers for electrical conductivity, matrix damage will sever the connection between fillers and result in a local conductivity loss. Monitoring composite conductivity changes can therefore give insight into the state of the matrix. Existing conductivity-based structural health monitoring methods are either insensitive to matrix damage or employ large electrode arrays. This research advances the state of the art by combining the superior imaging capabilities of electrical impedance tomography with conductive networks of nanofillers in the composite matrix. Electrical impedance tomography for damage detection in glass fiber/epoxy laminates with carbon black nanocomposite matrices is characterized by identifying a lower threshold of through-hole detection, demonstrating the capability of electrical impedance tomography to accurately resolve multiple through holes, and locating impact damage. It is found that through holes as small as 3.18 mm in diameter can be detected, and electrical impedance tomography 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. Finally, it is shown that electrical impedance tomography is also able to accurately locate impact damage. These research findings demonstrate the considerable potential of conductivity-based health monitoring for glass fiber reinforced polymer laminates with conductive networks of nanoparticles in the matrix.

Original languageEnglish (US)
Pages (from-to)100-109
Number of pages10
JournalStructural Health Monitoring
Volume14
Issue number1
DOIs
StatePublished - Jan 20 2015

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Mechanical Engineering

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