In-site experimental study on the effects of infrared thermal imaging technology on levee leakage detection | Scientific Reports

Oct 31, 2024

Scientific Reports volume 14, Article number: 26032 (2024) Cite this article

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Excessive seepage significantly affects the stability of levees during flood seasons. Recently, infrared thermal imaging technology has been proposed to detect the seepage leakage of levees for its simplicity, high efficiency and non-contact. However, previous studies mainly focused on theoretical and laboratory tests to verify its effect, which involve many assumptions and simplification. This paper aims to study the practical application effects of infrared thermal imaging technology on levee leakage detection. A typical embankment in Xiangyin County, Hunan Province is selected as the studied area, where a specific point containing water is considered as the potential leakage point. Then, DJI M300RTK UAV equipped with Zenith H20T gimbal is adopted to collect the visible and infrared images of the embankment’s leaking point. The visible and infrared image data collected at different times and at different measurement heights are analyzed to investigate the detection accuracy of infrared thermal imaging technology. Results show that the infrared thermal imaging technology can accurately identify the potential seepage leakage point of levees. Compared with the visible light recognition method, the infrared thermal imaging technology can identify the location and scope of leakage hazards more clearly and accurately at night. During the daytime, infrared detection is less effective than visible light method. Moreover, the measurement altitude between the drone and the target leakage points significantly affects the detection accuracy of infrared thermal imaging technology.

Levees are built for protecting property damages and casualties from river during flood seasons, particularly respect to excessive seepage under the foundation of levees1,2,3. However, most of the levees in China were built through replacement repair and reinforcement, which have very long history, and frequently are affected by animal and plant activities, resulting in frequent leakage hazards during the service. For example, piping, uplifting or heaving caused by underground seepage in the levee foundation can cause sand boils and loss of foundation materials, finally resulting in the failure of levees. Thus, quickly and accurately detecting levee leakage hazards is very important for levee safety and flood prevention and rescue of levees.

In recent years, various leakage detection methods have been proposed to identify potential dangers (e.g., piping and dam break) of levee engineering, including geological drilling, artificial visualization and geophysical exploration4. The geophysical detection method for detecting levee leakage dangers can generally been divided into natural electric field method5, high-density resistivity method6, transient electromagnetic method7, ground-penetrating radar method8, and temperature field method9. Among these geophysical detection method, the temperature field method based on infrared thermal imaging technology has become a research hotspot in the detection of seepage hazards in embankment projects for its simplicity, efficiency and non-contact10,11,12, – 13 .

With the generation of surface seepage phenomenon downstream of the embankment, the temperature characteristics of the region are changed. By means of UAV-carried infrared thermal imaging equipment, the infrared images of the embankment surface can be obtained. Then, the areas where temperature characteristics changed can be effectively identified to obtain the location of the leakage region14,15. To illustrate the validity of infrared thermal imaging technology on detecting the hidden dangers of levees, various theoretical, laboratory and numerical simulation studies have been conducted. In terms of theoretical analysis, Chen et al16. applied the virtual heat source method to study the existence of concentrated leakage channels in the fissured rock body of the dam foundation, and determined the location whether there is leakage around the borehole through the temperature field anomaly, which has provided an effective method for the leakage detection technology of embankment dams. In terms of laboratory tests, Inagaki et al17. carried out laboratory tests of concentrated leakage and random leakage in mortar specimens under different water temperature conditions, and verified the feasibility of infrared sensing leakage detection under the heating conditions of the water body. Song et al18. monitored the seepage condition of embankment, and proposed that the temperature can be an effective tool for judging the pre-emergent seepage condition of embankment. Wang et al19.designed a detection system by combining a UAV and infrared thermal imaging technology to identify early unstable seepage detection of a small reservoir dam, which determines early unstable seepage occurs by comparing the area of low temperature and high temperature regions. In terms of numerical simulation, Peng20initially investigated the detection of concentrated leakage infrared thermography in earth and rock dams, and found that the surface temperature of the leakage channel is lower than that of the normal dam body. Peng also found that the absolute and relative temperature differences between the leakage channel and the normal dam body increase with the water head. Zhang et al21. analyzed the temperature field of the double-layer embankment foundation in abnormal seepage conditions, and found that the low-temperature region can be observed in the seepage outlet. Jiang et al22. carried out the seepage-temperature-stress coupling calculation by using the software of FLAC3D to analyze the temporal and spatial evolutions of the seepage, temperature, and damage fields of the embankment and embankment base under the conditions of seepage and structural damages. Although the research on heat transfer from seepage in embankment engineering has been developed into theoretical analysis, laboratory tests and numerical simulation, the effect of simulating seepage is mostly achieved by artificially setting up the seepage channel, which involve many assumptions and simplification. Actually, the location of leakage hazards of levees has high randomness and complexity, and it is also affected by the surface vegetation. The practical effects of infrared thermal imaging technology in detecting levee leakage has not been involved and needs to be furtherly validated.

This paper carries out in-site experimental research to study the practical application effects of infrared thermal imaging technology on levee leakage detection. A typical embankment in Xiangyin County, Hunan Province is selected as the studied area, where a specific point containing water is considered as the potential leakage point. Then, DJI M300RTK UAV equipped with Zenith H20T gimbal is adopted to collect the visible and infrared images of the embankment’s leaking point. The visible and infrared image data collected at different times and at different measurement heights are analyzed to investigate the detection accuracy of infrared thermal imaging technology.

The theoretical basis of infrared thermography is Planck’s blackbody law:

Where λ and T are the wavelength of electromagnetic wave and the thermodynamic temperature of matter, respectively; h is Planck’s constant, which takes the value of 6.6260755 × 10−34 J∙s; k is Boltzmann’s constant, which takes the value of 1.380658 × 10−23 J/K; and c is the propagation speed of electromagnetic wave in vacuum, which takes the value of 2.99792458 × 108 m/s.

According to Planck’s blackbody radiation law, it is known that the intensity of infrared radiation of a substance is positively correlated with its own temperature, the higher the temperature, the greater the amount of infrared radiation23,24. The infrared thermal imaging camera is sensitive to infrared radiation. It can effectively obtain the thermal radiation pattern on the surface of the object, and converts the thermal radiation pattern into gray value data to generate thermal images. The imaging effect is affected by the temperature, the emissivity of the object, the absorption of the atmosphere and the reflection of the radiation by the surrounding objects and other factors. Due to the large difference in the specific heat capacity between the water and the solid material, when there is leakage on the surface of the building, the temperature distribution in the leakage area may be abnormal. In this way, the infrared thermal imager can clearly and directly show its characteristics.

Accurately analyzing the evolution of temperature field during the process of seepage of embankment engineering, and exploring the intrinsic connection between temperature field and seepage field are the theoretical basis of infrared detection technology for seepage hidden danger of embankment.

When seepage is generated within an embankment, the seepage pattern conforms to Darcy’s law. However, as for the heat transfer,, the heat transfer equation based on local heat balance can be given as follows25, where convective heat transfer on the contact surface between soil particles and seepage water is ignored:

Where \({c^T}\)is the effective specific heat capacity, J/(kg-K); T is the temperature, ℃; \({q^T}\)is the heat flux, W/m; \({\rho _0}\)is the base density of the fluid, kg/m3 ; \({c_w}\)is the fluid specific heat capacity, J/(kg-K); \(q_{v}^{T}\)is the volumetric heat source intensity, W/m3.

Yousefi et al26. studied the effect of seepage on the pressure and temperature fields in the dam body with Shamil dam as the object, and found that the temperature can reflect the seepage state better than the pressure; Cheng et al27. analyzed the heat transfer characteristics in the seepage process of earth and rock dams based on the theory of seepage heat transfer by using numerical simulation. He found that after the seepage flow is stabilized in the pore space, the temperature difference between saturated and unsaturated zones will be formed, which can be judged the location of the infiltration line in the dam body by the temperature.

Based on the abovementioned theories and research results, it can be initially confirmed that the seepage generated in the seepage channel will generate heat exchange with the surrounding solid materials. Then, temperature distribution differences can be generated in the overall embankment section or levee surface, which can be clearly and directly detected through the infrared thermal imaging camera. Then, statistical method is used to detect the abnormal temperature point. In detail, a temperature threshold can be set based on the mean and standard deviation. If the temperature values are within mean ± 2 times the standard deviation, the corresponding area are considered as normal temperature zone. If the temperature does not fall within the threshold range, the region cannot be identified as an abnormal temperature zone, indicating a potential seepage hazard point.

To investigate the practical detection effect of infrared thermal imaging technology. A typical embankment in Xiangyin County, Hunan Province is selected as the studied area (as shown in Fig. 1), where a specific point containing water is considered as the potential leakage point. The study area is located in Xiangyin County, Hunan Province, west of the east branch of Xiangjiang River. There is no abnormal heat source interference in the study area.

Study area.

In this experiment, a DJI M300RTK drone equipped with Zenith H20T gimbal is used to collect data on the backwater slope of a section of embankment. The infrared resolution of the Zenith H20T gimbal camera, mounted on the DJI M300 RTK drone, is 640 × 512 pixels. The thermal sensitivity (NETD, Noise Equivalent Temperature Difference) of the Zenith H20T is less than 50 mK, which can detect temperature differences as small as 0.05 °C, allowing it to detect very subtle temperature differences in levee seepage hazard detection. The detection band is 8–14 μm. The special location containing water accumulation was selected as the potential point of hidden dangers. The image data are obtained from visible light and infrared thermal imaging technology acquired by the UAV at different time periods and different measurement heights to investigate the detection accuracy of infrared thermal imaging technology for detecting hidden dike leakage dangers. As for the visible light image, if there is a leakage, the leaking area typically exhibits different colors compared to the surrounding environment. When the leaking region contains moisture, its light reflection properties are also different from the surrounding. In this way, the leakage area can be identified from the different colors or brightness in the image. Infrared thermal imaging technology is used in day and night respectively to obtain image information. Three measurement altitudes, i.e., 15 m, 20 m and 25 m, respectively, are set to explore the effects of infrared image shooting height on the detection accuracy.

Before the in-situ experiments, ambient temperature and the water surface temperature of the river are measured. Then, visible light and infrared thermal imaging technology is used to obtain the temperature distribution with specific testing conditions, as shown in Table 1. It can be seen that due to the difference in the specific heat capacity of the water and the soil, there is a significant difference in the high and low temperature zones during the day and at night. During the daytime, the soil temperature is higher than that of the water. However, the soil temperature is lower than that of water at night.

The visible light images of the study area for Case I obtained from different measurement heights are shown in Fig. 2. It can be seen that the study area contains a variety of landforms such as lush vegetation, sparsely vegetated areas, bare sand piles and holes containing water.

Visible light image for Case I.

Figure 3 shows the visible light images of the study area for Case II. As for the Case II, there is no leakage points occurred in the study area, most of which is covered by vegetations. However, the vegetation is extremely unevenly distributed, where some surface is bare and vegetation is not covered.

Visible light image for Case II.

From Figs. 2 and 3, it can be seen that the visible light image can clearly show the difference of hidden danger on the bare slope, but for the vegetation covered area, the visible light image cannot clearly show the hidden leakage point. Figures 4, 5, 6 and 7 show the visible light and infrared thermal radiation images of potential leakage points in the daytime and at night. As for the infrared thermal imaging technology, the infrared images can effectively show the temperature difference and clearly present the difference of hidden danger. However, due to the difference of thermal radiation between the bare land and the vegetation distribution area, there is interference in the detection results, as shown in Fig. 6(a)-6(c). Compared with the infrared images collected at night (see Figs. 4 and 6), it is obvious that the distribution of temperature for case I in the daytime is relatively complicated. Further deep-level image processing and machine learning are required to accurately identify the hidden danger areas and reduce the error. As shown in Fig. 4(a), when the height between the UAV and the surface of the measured area is set as 15 m in the daytime, the bare ground in the study area is in a high-temperature zone, with the highest temperature of 26.2℃, which is higher than the ambient temperature. The waterlogged area and the vegetation area are in the low-temperature zone, and the lowest temperature is located in the vegetation area, which equals to 14.7℃. The lowest temperature in the waterlogged area is 15.3℃.

Infrared images for Case IV in the daytime.

As can be seen in Figs. 4 and 5, due to the difference in the distribution of vegetation on the embankment surface, the infrared image information of the normal embankment in the daytime also exists in a variety of temperature zones, and there is the phenomenon of “leakage-like”, which affects the accuracy of the identification of the leakage. For example, very small differences of temperature in Fig. 4(a) and 5(a) are observed in the area of lush vegetation. The temperature is around 14.5℃ in Fig. 4(a), which is slightly lower than the temperature with a value of 15.3 C in the leakage area in Fig. 5(a).

Infrared images for Case V in the daytime.

From Fig. 6, it is obvious that the infrared thermal radiation images at night is more concise compared with that in the daytime. After the overall decrease of the temperature in the no-water body interference area (i.e., the non-hidden area), the influence of vegetation cover on the temperature distribution of embankment slopes decreases significantly. In this case, the hidden seepage area is a high-temperature area (see Fig. 6). The leakage points are more prominent in the whole image compared with that in daytime (see Fig. 4). As shown in Fig. 6(a), when the height between the UAV and the surface of the measured area is set as 15 m at night, the waterlogged area within the typical zone obtained is a significantly high temperature zone, with a maximum temperature of 14.6 °C, which is higher than the ambient temperature but lower than the temperature of the water surface of the river at the same period. As for the other area, except for the extremely low temperature of a few exposed points (8.3 °C), the temperature slightly lower than the ambient temperature. Compared Figs. 6 and 7, it can be seen that under the normal conditions (i.e., without leakage), the infrared image of the embankment at night is uniformly distributed, and the temperature distribution of each region is relatively average with no temperature difference areas. However, when there is a potential seepage, the infrared image shows obvious high temperature area, where the temperature is greatly different from that of the surroundings.

Infrared images for Case IV at night.

Infrared images for Case V at night.

Table 2 shows the results of identified characteristics of potential leakage points. The leakage area diameter d and original image width L can be used to illustrate the accuracy of seepage leakage detection. d and L are the pixel width obtained from the image. It can be seen that through the visible image, the potential leakage area d/L obtained at the measurement heights of 15 m, 20 m and 25 m are 0.026, 0.020 and 0.018, respectively. By using infrared thermal imaging technology, the values of d/L in the daytime are 0.025, 0.017 and 0.016, respectively, which are obviously smaller than that obtained from visible images. However, the values of d/L at night are 0.029, 0.024 and 0.018, respectively, which are obviously larger than that in the daytime. Comparing the values of d/L of infrared images and visible images at different times of the day at the same altitude, it is obvious that the values of d/L obtained from the infrared images at night have the maximum values. The d/L obtained from the infrared images in the daytime have the minimum values. It shows that the performs better at night in identifying the hidden leakage hazards.

Therefore, compared with the daytime, the infrared image features at night can show the hidden seepage hazards more accurately. Totally, the infrared thermal imaging technology performs better in identifying the hidden leakage hazards in levee projects at night.

As shown in Figs. 8 and 9 show the images of simulated low temperature leakage point during the day obtained from visible and infrared images, respectively. A rectangular ice pack with a size of 10 cm×16 cm is added in the lower right corner of the study area to simulate the low temperature leakage point during the day. The actual temperature on the surface of the ice pocket during the test is 8℃. Figure 8(a)-8(c) show that the white ice pack is obviously observed in the vegetation area and could be detected in the visible image. However, in the actual leakage situation, the leakage that occurred in the vegetation-covered area is easily obscured by the vegetation and extremely difficult to be captured in the visible image. As the relative altitude between the UAV and the area measured rises, the tiny objects are gradually blurred in the image. Compared with the corresponding infrared image (Fig. 9), it can be seen that when the temperature difference between the leakage area and the non-leakage area is large, the infrared image can show its shape feature and area size. When the relative height between the UAV and the area is increased, although the imaging size of the hidden hazardous area is reduced within the image, its shape feature still can be identified and marked by the thermal imager due to the temperature feature, making more accurate detection.

Visible light image for Case III.

Infrared images for Case VI.

From Fig. 6(a)-6(c), as the measurement height between the UAV and the detected area increases from 15 m to 25 m, the size of the feature area in the image becomes smaller, and the maximum temperature stays around 14.5 °C, higher than the outside ambient temperature. However, the minimum temperature of the area rises, and the average temperature also rises, moving closer to the ambient temperature value. The reason for such changes may be that when the relative height increases, the thermal radiation induction has some degree of attenuation and converges with the ambient temperature. The temperature measurements in images Fig. 4(a)-4(c) show that the attenuation is extremely obvious, and the temperature values are even lower than the ambient temperature above 20 m. The reason for this sudden change is that, compared with the detection range at the relative altitude of 15 m, the low-temperature area (vegetation covered area) is introduced in large quantities when the altitude is raised, which results in a larger attenuation of the overall temperature.

It can also be seen from Table 2 that the measurement height has great effects on the detection accuracy of potential leakage area. Figure 10 shows the relationship of measurement heights and d/L. It is clear that the values of d/L decreases with the measurement height. When the measurement height of infrared thermal imaging technology increases to 25 m, the values of d/L obtained from infrared images in the daytime and at night are similar. When the measurement height of infrared images is set as 15 m at night, the d/L has the maximum value of 0.029, indicating that in this case, the infrared thermal imaging technology can accurately identify hidden leakage area. As the relative height between the UAV and the detection area increases, the detection range obviously increases at the same time. The potential seepage area is relatively reduced and becomes harder to find. Therefore, it is necessary to find the optimal measurement height considering the detection accuracy and detection efficiency at the same time.

Effects of measurement heights on infrared detection accuracy.

This paper selected a typical embankment in Xiangyin County, Hunan Province to study the practical application effects of infrared thermal imaging technology on levee leakage detection. A series of in-site experiments were conducted to detect potential leakage area by using DJI M300RTK UAV equipped with Zenith H20T gimbal. The visible and infrared image data collected at different times and at different measurement heights are analyzed to investigate the detection accuracy of infrared thermal imaging technology. The following conclusions are drawn from the results and analysis:

(1) The infrared image features at night are more concise and clearer than those in the daytime, which can identify the hidden seepage area more effectively.

(2) As the relative height between the UAV and the detection area increases, the information contained within a single image increases, there is a proportional attenuation of the intensity of the thermal radiation, and the requirements for the size of the hidden feature area and the temperature difference between it and the normal area increase.

(3) The measurement height of infrared thermal imaging technology has great effects on the detection accuracy of potential leakage area in levee project. When the measurement height of infrared thermal imaging technology increases to 25 m, the detected accuracy obtained from infrared images in the daytime and at night are similar. When the measurement height of infrared images decreases at night, the infrared thermal imaging technology can accurately identify hidden leakage area. It is necessary to find the optimal measurement height considering the detection accuracy and detection efficiency at the same time.

All data generated or analyzed during this study are included in this published article.

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This work was supported by the Water Science and Technology Project of Hunan Province, (Project No. XSKJ2021000-9 and Project No. XSKJ2021000-14). The authors are also grateful to the anonymous reviewers for their helpful comments and advice.

Hunan Institute of Water Resources and Hydropower Research, 370 Shaoshan North Road, Changsha, 410007, P. R. China

Xiang Wang, Jingwei Liang & Li Rongliang

Hunan Dam Safety and Disease Prevention Engineering and Technology Research Centre, 370 Shaoshan North Road, Changsha, 410007, P. R. China

Xiang Wang, Jingwei Liang & Li Rongliang

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Wang xiang wrote the main manuscript. Liang jingwei and Li Rongliang conducted the in-site experment and data collection and revised the manuscript.

Correspondence to Xiang Wang.

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Wang, X., Liang, J. & Rongliang, L. In-site experimental study on the effects of infrared thermal imaging technology on levee leakage detection. Sci Rep 14, 26032 (2024). https://doi.org/10.1038/s41598-024-77383-w

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Received: 16 April 2024

Accepted: 22 October 2024

Published: 29 October 2024

DOI: https://doi.org/10.1038/s41598-024-77383-w

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