Quantitative Infrared Thermography to Evaluate the Humidification of Lightweight Concrete
Abstract
:1. Introduction
2. Methodology
2.1. Test Procedures
2.2. Imaging Processing
- Step I
- The average surface temperature of the entire specimen was considered, and the statistic t-test was used to compare consecutive thermal images. With Step I, a reduction by one-half was expected.
- Step II
- Step II Only the average surface temperature of the boxes G, H, and I was considered, as the lower area of the specimen was deemed to be the most relevant in the phenomenon. Once more, the statistic t-test was used to compare consecutive thermal images aiming for a reduction by one-quarter.
3. Results
3.1. Phase 1—Pre-Processing
3.1.1. Sample Reduction
3.1.2. Surface Temperature over Time
3.2. Phase 2—Data Processing
3.2.1. Statistical Descriptive Analysis
3.2.2. Analysis Based on Image Subtraction
3.2.3. Analysis Based on Index TI
4. Conclusions
- The second phase of the methodology was the data processing. It was based on three methods: statistical descriptive analysis, image subtraction, and definition of a thermal index. The use of a box-plot representation over time considering the entire specimen was very interesting because the variability of the temperatures at certain moments of the experiment could be observed. It was found that the variability increased with the humidification process due to the increase of the wet area. The information provided by the outliers confirmed this conclusion, as their number tended to decrease throughout the test. Analyzing the box-plot representations of the boxes located in the central region of the specimen gave additional information regarding temperature variations at different levels, allowing an understanding of the water level achieved by the absorbed water at different moments of the experiment. In this case study, the temperature range in the lowest box, at different periods in time, pointed to the largest variations in the first hours, tending to stabilize at the end of the humidification.
- Image subtraction was a very interesting technique if the first image was used as a reference. When subtracting the previous image, the results were not so clear. This result confirmed that time is a key parameter to characterize the humidification phenomenon. Image subtraction is the most useful method if one intends to quantify the temperature differences due to moisture.
- The thermal index, TI, ranging between 0 and 1, allowed quantifying the cooling rate of the specimen. The three phases already identified through other methods were also highlighted by this index, as well as the confirmation of the cooling effect at the bottom of the specimen. However, more information could be obtained, as it was possible to identify that the effect of moisture on the surface temperature of the specimen only occurred after the first three hours.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Dimensions | 0.28 × 0.21 × 0.075 m3 |
Dry density | 1351 kg/m3 [34] |
Water absorption coefficient | 4.521 × 10−3 g/(mm2∙h0.5) [35] |
Emissivity | 0.91 [36] |
Measuring range | −20 °C to 100 °C |
Resolution | 0.06 °C at 30 °C, 60 Hz |
Accuracy | ±2 °C or ±2% |
Detector | FPA (microbolometer) |
Spectral range | 8 and 14.0 μm |
IFOV | 1.2 mrad |
Thermal resolution | 320 × 240 pixels |
Field of view | 22° × 16° |
Box A | Box B | Box C | Box D | Box E | |
---|---|---|---|---|---|
Mean | 16.9 | 16.9 | 16.9 | 16.5 | 16.5 |
Median | 16.9 | 16.9 | 16.9 | 16.5 | 16.5 |
SD | 0.06 | 0.06 | 0.06 | 0.09 | 0.09 |
Skewness coefficient | −0.16 | 0.07 | −0.03 | −0.19 | −0.18 |
Maximum | 17.0 | 17.1 | 17.1 | 16.8 | 16.7 |
Minimum | 16.7 | 16.7 | 16.7 | 16.3 | 16.3 |
Box plot | | | | | |
Histogram | |||||
Box F | Box G | Box H | Box I | Total | |
Mean | 16.6 | 15.2 | 15.1 | 15 | 16.4 |
Median | 16.6 | 15.2 | 15.1 | 15 | 16.6 |
SD | 0.10 | 0.19 | 0.19 | 0.22 | 0.63 |
Skewness coefficient | −0.10 | −0.01 | −0.07 | −0.05 | −1.07 |
Maximum | 16.9 | 15.6 | 15.5 | 15.5 | 17.2 |
Minimum | 16.3 | 14.7 | 14.6 | 14.5 | 14.5 |
Box plot | | | | | |
Histogram |
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Barreira, E.; Almeida, R.M.S.F.; L. Simões, M.; Rebelo, D. Quantitative Infrared Thermography to Evaluate the Humidification of Lightweight Concrete. Sensors 2020, 20, 1664. https://doi.org/10.3390/s20061664
Barreira E, Almeida RMSF, L. Simões M, Rebelo D. Quantitative Infrared Thermography to Evaluate the Humidification of Lightweight Concrete. Sensors. 2020; 20(6):1664. https://doi.org/10.3390/s20061664
Chicago/Turabian StyleBarreira, Eva, Ricardo M.S.F. Almeida, Maria L. Simões, and Daniela Rebelo. 2020. "Quantitative Infrared Thermography to Evaluate the Humidification of Lightweight Concrete" Sensors 20, no. 6: 1664. https://doi.org/10.3390/s20061664
APA StyleBarreira, E., Almeida, R. M. S. F., L. Simões, M., & Rebelo, D. (2020). Quantitative Infrared Thermography to Evaluate the Humidification of Lightweight Concrete. Sensors, 20(6), 1664. https://doi.org/10.3390/s20061664