A Novel Methodology for Spatial Damage Detection and Imaging Using a Distributed Carbon Nanotube-Based Composite Sensor Combined with Electrical Impedance Tomography

  • Hongbo Dai
  • Gerard J. Gallo
  • Thomas Schumacher
  • Erik T. Thostenson
Article

DOI: 10.1007/s10921-016-0341-0

Cite this article as:
Dai, H., Gallo, G.J., Schumacher, T. et al. J Nondestruct Eval (2016) 35: 26. doi:10.1007/s10921-016-0341-0

Abstract

This paper describes a novel non-destructive evaluation methodology for imaging of damage in composite materials using the electrical impedance tomography (EIT) technique applied to a distributed carbon nanotube-based sensor. The sensor consists of a nonwoven aramid fabric, which was first coated with nanotubes using a solution casting approach and then infused with epoxy resin through the vacuum assisted resin transfer molding technique. Finally, this composite sensor is cured to become a mechanically-robust, electromechanically-sensitive, and highly customizable distributed two-dimensional sensor which can be adhered to virtually any substrate. By assuming that damage on the sensor directly affects its conductivity, a difference imaging-based EIT algorithm was implemented and tailored to offer two-dimensional maps of conductivity changes, from which damage location and size can be estimated. The reconstruction is based on a newly defined adjacent current–voltage measurement scheme associated with 32 electrodes located along the boundary of the sensor. In this paper, we evaluate our methodology first by introducing well-defined damage where sections are either removed or narrow cuts are made on a series of sensor specimens. Finally, a more realistic damage scenario was investigated to show the capability of our methodology to detect impact damage on a composite laminate. The resulting EIT maps are compared to visual inspection and thermograms taken with an infrared camera.

Keywords

Distributed sensing Carbon nanotube Composite materials Nonwoven fabric Electrical impedance tomography  Non-destructive evaluation Damage detection Difference imaging 

Supplementary material

10921_2016_341_MOESM1_ESM.docx (433 kb)
Supplementary material 1 (docx 434 KB)

Funding information

Funder NameGrant NumberFunding Note
Directorate for Engineering
  • 1234830

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Hongbo Dai
    • 1
    • 5
  • Gerard J. Gallo
    • 2
    • 5
  • Thomas Schumacher
    • 3
  • Erik T. Thostenson
    • 2
    • 4
    • 5
  1. 1.Civil and Environmental EngineeringUniversity of DelawareNewarkUSA
  2. 2.Mechanical EngineeringUniversity of DelawareNewarkUSA
  3. 3.Civil and Environmental EngineeringPortland State UniversityPortlandUSA
  4. 4.Materials Science & EngineeringUniversity of DelawareNewarkUSA
  5. 5.Center for Composite MaterialsUniversity of DelawareNewarkUSA

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