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Nofar et al. (
2009
), and Kostopoulos et al. (
2009
). CNT concentrations as low as
0.1 w% was sufficient for producing electrically conductive, epoxy-based com-
posites (Thostenson and Chou
2002
; Thostenson and Chou
2006
; Thostenson and
Chou
2008
).
Despite these advances in creating skin-like thin films that are piezoresistive,
strain sensing could only be accomplished in an average sense. A resistivity
measurement was directly correlated to strains being experienced by the under-
lying structure (i.e., at least on the surface). However, this strain measurement was
averaged over the entire surface area or measurement area of the film. Yet,
structural damage including cracks, corrosion, and impact were localized phe-
nomena. An ''averaged'' strain measurement may not be able to detect such
damage (i.e., depending on the size of damage and measurement area).
Instead, one could leverage the fact that the electrical resistivity (or equiva-
lently conductivity) of every location in the film is calibrated to strain. Work by
Hou et al. (
2007b
) and Loh et al. (
2009
) showed that an electrical impedance
tomography (EIT) algorithm (Brown
2003
) could be used for mapping the spatial
conductivity distribution of CNT-based thin films. To produce this conductivity
map without having to probe every location in the film, EIT relied on a set of
instrumented electrodes along the boundaries of the thin film. This defined the
sensing area. Then, EIT utilized boundary current input and voltage measurements
for reconstructing the spatial conductivity distribution of the thin film (Borcea
2002
; Brown
2003
). By nature, the EIT inverse problem is an ill-posed problem,
and one set of boundary voltage measurements would be insufficient for deter-
mining the spatial conductivity map of the sensing area (Holder
2005
). Thus,
electrical current was applied to numerous boundary electrodes, and sets of
boundary voltage measurements were obtained for each current injection case.
Since thin film conductivity (or resistivity) was correlated to applied strain, pH, or
other damage phenomena (Loh et al.
2007
,
2008
; Loh
2008
), the spatial con-
ductivity maps were directly related to spatial damage in the underlying structure.
Previous works by Hou et al. (
2007a
,
b
) validated the EIT technique for spatial
conductivity mapping of the aforementioned layer-by-layer CNT-based thin films.
Square 25 9 25 mm
2
SWNT-based thin films were instrumented with boundary
electrodes, and EIT was used to obtain baseline conductivity maps of these films.
Then, selected regions on the film surface were intentionally etched and removed
so as to create straight, diagonal, and L-shaped cuts (Hou et al.
2007b
). These cuts
formed regions of zero conductivity in the film and were used for simulating some
change or extreme damage. After mechanical etching, EIT was conducted again to
obtain the relative change in thin film spatial conductivities. It was found that the
spatial conductivity maps visually represented that of the actual films, and they
could be used for identifying the locations of these cuts (Hou et al.
2007a
,
b
). It
was also shown that the EIT-estimated spatial conductivities were within 2 % error
as compared to experimental measurements of the same film and sensing area.
With the EIT algorithm validated, these carbon nanotube sensing skins were
then used for SHM and laboratory tests. For example, sensing skins were coated
onto aluminum plates and mounted in an impact testing apparatus. It was shown
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