the two extremities of the sample for a fixed current.
The signal injected at the top of the sample is a square waveform of 12 V of amplitude and 137 Hz frequency. This signal is compared to the signal received at the bottom of the sample in order to calculate de variation of the voltage during the desaturation process. An Average Waveform Generator incorporated to a digital oscilloscope (TiePie Handyscope HS5) is used. The same oscilloscope is used to record the evolution of the signal with a resolution of 12 bits and a sampling frequency of 10 kHz.
The thermal scene has been recorded with the same camera previously presented. IR images of the thermal scene are recorded at a frequency of 0.01 Hz. From each IR Image a surface area has been selected to highlight the temperature evolution of the limestone sample and the reference (crumpled aluminum-foil).
Finally, a mass balance allows to measure the mass loss during the experience.
Results and Discussion
In order to determine the most convenient ROI used to calculate the thermal response versus the saturation degree, those histograms are used to determine the relevance of the ROI’s by analyzing their statistical moments. Evolution of the mean temperature values versus the water content is presented in the figure 4.
Figure 4: Mean temperature values and its standard deviations for each ROI with fit curve model.
255Functional mathematical relation is highlighted. In addition, with ROI 3 the skewness value is closed to zero. The third and fourth order moments values are consistent with a Laplace-Gauss distribution. As a consequence, the reduction of the surface analysis gives a better standard deviation to mean value ratio.
Finally, for a better accuracy of the calibration protocol, the reduction of the analysis surface helps to prevent against the edge effect and the risk of the non-homogenization of the water in the porous media.
In order to avoid edge effects, the calibration between the sample saturation and the IR response are defined by a fit function representing the evolution of the average temperature values of the ROI 3.
The second set of results corresponds to the experiments designed to survey the desaturation of the materials via electric and infrared imaging methods as well as by gravimetric measurements.
After data treatment the results are presented in the form of curves representing the evolution of electrical resistivity (deduced from the non-invasive electrodes) and temperature variation according to saturation, figure 5.
Figure 5: Thermal and electrical results of the desaturation experience showing the different zones related with each step of the desaturation process.
The results show that the saturation interval for which the IR and electric imaging method provides usable information is between 20 and 50 % and between 35 and 90 % respectively.
The interpretation of the results helps to define the phenomenological model of desaturation.
The results allow to identify six main steps corresponding to the desaturation dynamics model presented in the figure 5. The steps of the model correspond to the different zones reported in the figure.
ZONE 1: During this stage, there is a drastic temperature drop of the sample. This is due to the evaporation of the water covering the surface of the sample.
ZONE 2: During this stage, no significant temperature variation on the sample surface is detected. But in the same way, the water losses are detected by the electrical resistivity measurement. The water content decreasing (calculated from the mass measurement) is logically observed by the electrical resistivity increase. During this stage, the two used methods show the water redistribution in the volume probably through a stable hydrous transfer at the surface of the sample induced by the thermal equilibrium at the surface.
ZONE 3: During this stage, temperature and electrical resistivity increase quickly. This is due to the removal of the waterfront inwards of the sample and the gradual loss of the water volume.
ZONE 4: During this stage, only the temperature measurements seems to be able to characterize the sample saturation. A limit electrical resistivity is reached during the stage. This behavior is probably induced by the loss of electrical continuity in the volume (distribution of water in the form of clusters).
ZONE 5: Due to the gradual evaporation of the water from the unconnected clusters, a constant temperature is reached during this stage too.
ZONE 6: The sample is dry and as consequence non relevant signal is detected for both methods.
The results for the thermal response of the dynamic desaturation experiment allow us to analyze the validity of the calibration of IR responses based on the saturation calculated in a static frame.
In addition these results show that the combination of electric resistivity and IR imaging technics presents some advantages compared to others NDT as NMR or EFD (also known as Susi-R) that could be found in the literature (EN 16682, 2017, V. Di 256Tullio et al., 2010). The advantages and drawbacks of each method are presented in the table 2.
Table 2: Advantages and drawbacks of common NDT (EN 16682, 2017).
| Technics | Advantages | Drawbacks |
| IR | Contact free, portability, easy to use and diagnosis at metric scale | Mandatory calibration and sensitivity to thermal environment |
| Electric resistivity | Volumetric analysis from millimetric to metric scale | Mandatory calibration and contact analysis |
| Susi-R | Portability, easy to use, quick diagnosis and centimetric depth analysis | Mandatory calibration, contact analysis and roughness sensitivity |
| NMR | Contact free measurement and centimetric depth analysis | Heavy data treatment and measurements affected by metals |
Indeed, due to the characteristics of the IR imaging method concerning its portability and ease of use as well as the quick diagnosis at metric scale, combined to the volumetric measures capabilities of the electric imaging method, the combination of those two imaging technics makes a highly appropriate and powerful proceeding for water content characterization on stone building materials.
Conclusions
The complementarity of the infrared thermography and electrical imaging methods is highlighted by showing the different relevant saturation ranges of both methods. This allows to establish the basis to the creation of a protocol which can be used to monitor the effects of changes of water content in the porous media. Illustration is given
