  Using thermography as a nondestructive method for subsurface detection of the
concrete structure has been developed for decades. However, the performance of
current practice is limited due to the heavy reliance on the environmental
conditions as well as complex environmental noises. A non-time-series method
suffers from the issue of solar radiation reflected by the target during
heating stage, and issues of potential non-uniform heat distribution. These
limitations are the major constraints of the traditional single thermal image
method. Time series-based methods such as Fourier transform-based pulse phase
thermography, principle component thermography, and high order statistics have
been reported with robust results on surface reflective property difference and
non-uniform heat distribution under the experimental setting. This paper aims
to compare the performance of above methods to that of the conventional static
thermal imaging method. The case used for the comparison is to detect voids in
a hollow concrete block during the heating phase. The result was quantitatively
evaluated by using Signal-to-Noise Ratio. Favorable performance was observed
using time-series methods compared to the single image approach.
