Water leakage detection method and water leakage determination device

Abstract

To provide a water leakage detection method capable of early detecting the occurrence of water leakage inside a structure.SOLUTION: A water leakage detection method for determining whether water leakage occurs in a structure includes: an arrangement step of arranging a heating material 10 which generates heat by reaction with moisture at a position having the possibility of appearance of water due to the water leakage; an image acquisition step of acquiring temperature distribution images which indicate a temperature distribution in a region including the heating material 10 over time; and a display step of making a display part sequentially display the temperature distribution images.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a water leakage detection method for determining whether or not water leakage has occurred in a structure, and a water leakage determination device for determining whether or not water leakage has occurred. [Background technology]

[0002] In the past, through cracks such as construction joints and thermal cracks have been observed in structures such as tunnels made of reinforced concrete. When through cracks occur in the outer components of tunnels, water leakage may occur, causing and accelerating various types of deterioration, so early detection of water leakage is important. On the other hand, there is a limit to regular visual inspections of the inside of a dark tunnel, for example, so various technologies that lead to early detection have been proposed.

[0003] For example, Patent Document 1 discloses a self-powered water leakage detection device for underground facilities, which includes a self-powered water leakage detection sensor that generates power when water leaks from an underground facility, and a display device that displays the occurrence of water leakage based on the generated voltage or current from the self-powered water leakage detection sensor. This self-powered water leakage detection device is installed, for example, in a tunnel, and has a container that stores water leaking from cracks in the tunnel. Two electrodes with different ionization tendencies are arranged in the container, and the two electrodes come into contact with the leaking water and function as a battery, activating the self-powered water leakage detection sensor and displaying the occurrence of water leakage on the display device. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2013-167550 A Summary of the Invention [Problem to be solved by the invention]

[0005] In the above Patent Document 1, the occurrence of a water leak is displayed on a display device installed at the site. That is, workers in the tunnel determine whether or not there is a water leak by checking whether or not the display device emits light. In this way, if the presence or absence of a water leak must be visually confirmed at the site of the water leak, there is a problem in that it is difficult to perform the confirmation work itself quickly.

[0006] Therefore, an object of the present invention is to provide a water leakage detection method capable of detecting the occurrence of water leakage in a structure at an early stage. [Means for solving the problem]

[0007] In response to the above-mentioned problems, the present invention provides a water leakage detection method for determining whether or not a water leak is occurring in a structure, and is characterized by comprising a placement step of placing a heat generating material that generates heat by reacting with moisture in a location where water may be generated due to leakage, an image acquisition step of acquiring, over time, a temperature distribution image showing the temperature distribution in an area including the heat generating material, and a display step of sequentially displaying the temperature distribution images on a display unit.

[0008] Here, in the arranging step, a plurality of the heat generating materials are arranged along a direction away from a position where water leakage may occur.

[0009] In addition, the water leakage determination device of the present invention is a water leakage determination device that determines whether or not a water leak is occurring in a structure, and is characterized in that it is arranged in a position where water may occur due to leakage, and includes an image acquisition unit that acquires over time a temperature distribution image showing the temperature distribution of an area including a heat generating material that generates heat by reacting with moisture, an extraction unit that extracts a temperature change area from the temperature distribution image where a temperature change has occurred, and a determination unit that determines whether or not the temperature change in the temperature change area is due to heat generation by the heat generating material.

[0010] Here, it is preferable that the temperature distribution image acquired by the image acquisition unit is acquired by a thermo camera mounted on a moving body. Also, it is preferable that the water leakage determination device includes a machine learning unit equipped with a learning model generated based on a plurality of temperature distribution images and a determination result of whether or not water leakage has occurred, and the determination unit uses the learning model to determine whether or not the temperature rise in the temperature change area is due to heat generation by the heat generating material. Furthermore, it is preferable that the water leakage determination device includes a temperature detection unit that detects the temperature in the temperature change area, and the determination unit determines whether or not the temperature rise in the temperature change area is due to heat generation by the heat generating material by comparing the detected temperature in the temperature change area with a preset threshold value. Effect of the Invention

[0011] In this way, in the water leakage detection method of the present invention, a heat generating material that generates heat by reacting with moisture is placed in a position where water may be generated due to leakage, temperature distribution images showing the temperature distribution in the area including the heat generating material are obtained over time, and the temperature distribution images are displayed sequentially on the display unit. In this way, the phenomenon of water leakage in a structure, which is difficult to detect, is visualized by the temperature distribution images using the heat generating material, making it possible to detect the occurrence of water leakage at an early stage.

[0012] In particular, by arranging multiple heat generating materials in a direction away from the location where water leakage may occur, the timing at which the multiple heat generating materials 10 start to generate heat can be staggered, thereby lengthening the total heat generation period.

[0013] The water leakage determination device also includes an image acquisition unit that acquires a temperature distribution image over time that shows the temperature distribution in an area including a heat-generating material, an extraction unit that extracts a temperature change area in the temperature distribution image where a temperature change has occurred, and a determination unit that determines whether or not the temperature change in the temperature change area is due to heat generation by the heat-generating material, thereby making it possible to automatically determine whether or not a water leakage has occurred in a structure.

[0014] In particular, if the temperature distribution image is acquired by a thermo camera mounted on a moving body, continuous images within the structure can be acquired over time. Note that by using a learning model generated by machine learning to determine whether or not the temperature rise in the temperature change area is caused by the heat generation of the heat-generating material, it is possible to appropriately determine which of the temperature change areas is caused by the heat generation of the heat-generating material. In addition, by comparing the difference value of the detected temperature in the temperature change area with a preset threshold value to determine whether or not the temperature rise in the temperature change area is caused by the heat generation of the heat-generating material, it is also possible to determine which is caused by the heat generation of the heat-generating material. [Brief description of the drawings]

[0015] [Figure 1] 1 is a diagram showing an example of the inside of a tunnel to which a water leakage detection method according to an embodiment is applied; [Diagram 2] FIG. 13 is a diagram showing an example of the arrangement of heat generating materials inside a tunnel. [Diagram 3] FIG. 2(a) is a diagram showing an example of a heat generating material, and FIG. 2(b) is a diagram showing another example of a heat generating material. [Figure 4] FIG. 1 is a block diagram showing an example of a water leakage determination device. [Diagram 5] FIG. 1 is a diagram showing a vehicle traveling in a tunnel. [Figure 6] FIG. 13 is a schematic diagram showing an example of a temperature distribution image captured inside a tunnel. [Figure 7] 13(a) and 13(b) are schematic diagrams showing an example of a temperature distribution image. [Figure 8] FIG. 1A is a diagram showing an example of the arrangement of heat generating materials for extending the heat generating period, and FIG. 1B is a graph showing the extended heat generating period. [Figure 9] FIG. 1 is a diagram showing an example of application of a heat generating material at a construction site. [Figure 10] 4 is a schematic diagram showing an example of a temperature distribution image displayed on a display unit. FIG. [Figure 11] FIG. 13 is a diagram showing an example of application of a heat generating material indoors. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] Fig. 1 is a diagram showing an example of the inside of a tunnel T to which a water leakage detection method according to an embodiment of the present invention is applied. As shown in Fig. 1, a heat generating material 10 is arranged on a wall surface W inside the tunnel T. The heat generating material 10 is arranged at three locations along the vertical direction of the wall surface W.

[0018] The positions and number of heat generating materials 10 attached to the wall surface W are not particularly limited, but from the viewpoint of water leakage, the further down the wall surface W the more likely the leaking water is to collect and the more likely it is to be detected. For this reason, it is desirable to arrange the heat generating materials 10 so that they occupy a large portion of the lower portion of the wall surface W. Also, multiple heat generating materials 10 may be arranged vertically or horizontally, or a single heat generating material 10 extending in each direction may be arranged.

[0019] The heat generating materials 10 are disposed in locations where water leakage may occur in a structure such as a tunnel T. Specifically, as shown in Fig. 1, the heat generating materials 10 are disposed so as to straddle a joint L of a structure such as a tunnel T and extend in the horizontal direction across the joint L. The vertical spacing between the heat generating materials 10 is not particularly limited.

[0020] Since the construction joints L are discontinuous parts of the tunnel T, they are more likely to leak than other parts. For example, the construction joints L at parts where there is spring water in the ground behind them are more likely to leak. Therefore, the heat generating material 10 is preferentially placed at the construction joints L where leakage is likely to occur. Note that the heat generating material 10 does not necessarily have to be placed at all of the construction joints L. Furthermore, since leakage can occur at parts of the wall surface W other than the construction joints L, the heat generating material 10 may be placed at parts other than the construction joints L.

[0021] 2 is a diagram showing an example of the arrangement of heat generating materials 10 inside tunnel T, and is a view of the inside of tunnel T seen from above. If the overall length of tunnel T itself is long, the number of construction joints L also increases. Therefore, as many heat generating materials 10 as possible should be arranged along the direction in which tunnel T extends. Note that multiple heat generating materials 10 may be arranged at different positions in the vertical and horizontal directions.

[0022] 3(a) is a diagram showing an example of the heat generating material 10. The heat generating material 10 is configured to have an attachment part 11 and a heat generating part 12 provided on the attachment part 11. The attachment part 11 is an adhesive member formed in a sheet shape that can be attached to a wall surface W, for example.

[0023] The heat generating portion 12 is a heat generating element such as quicklime (CaO) or iron (Fe). For example, when quicklime reacts with moisture, the following reaction occurs. CaO+H2O=Ca(OH)2+ reaction heat Furthermore, when iron reacts with moisture, the following reaction occurs: Fe+1.5H2O=Fe(OH)3+ reaction heat

[0024] The reaction heat is generated when the heating element comes into contact with moisture, and it is highly likely that this moisture is due to water leakage from the wall surface W. By utilizing the generation of this reaction heat, it is possible to estimate that the area in the temperature distribution image described below where the temperature has risen due to the reaction heat is the area where water leakage has occurred. The temperature of the reaction heat is about 60°C, but is not necessarily limited to this temperature.

[0025] 3(b), the heat generating material 10a may be a spray material that is sprayed onto the wall surface W, or a coating material that is applied onto the wall surface W. For example, the heat generating material 10a may be disposed on the wall surface W by an operator spraying a spray material or coating material that contains a heat generating element such as quicklime or iron onto the wall surface W using a sprayer.

[0026] 4 to 7, a procedure for determining whether or not a water leak has occurred in the tunnel T will be described in detail. In order to determine whether a water leak has occurred, a camera (imaging unit) 21 is mounted on the leading vehicle of vehicles 20 traveling in the tunnel T, and the determination is made using images captured by the camera 21. Images acquired from different vehicles 20 are collectively managed by the water leakage determination device 100.

[0027] 4 is a block diagram showing an example of the water leakage determination device 100. The water leakage determination device 100 is a device that is installed outside the tunnel T and used by an administrator. The water leakage determination device 100 is capable of communicating with, for example, a vehicle 20 traveling through the tunnel T via a network 300.

[0028] FIG. 5 is a diagram showing a situation in which the vehicle 20 is traveling inside the tunnel T, and FIG. 6 is a diagram showing an example of a temperature distribution image captured inside the tunnel T by the vehicle 20. As shown in FIG.

[0029] As shown in Fig. 5, the vehicle 20 captures an image inside the tunnel T. Specifically, a camera 21 mounted on the vehicle 20 traveling inside the tunnel T continuously captures an image (see Fig. 6) of the front side in the traveling direction of the vehicle 20. Here, the camera 21 is, for example, a thermal camera, and the captured image is a temperature distribution image inside the tunnel T.

[0030] The temperature distribution image captured by the camera 21 is transmitted to the water leakage determination device 100 via a network 300. The water leakage determination device 100 is configured to include a communication unit 110, a control unit 120, a display unit 130, and a storage unit 140.

[0031] The communication unit 110 performs various communications between the water leakage determining device 100 and the vehicle 20 via the network 300. Specifically, the communication unit 110 communicates with a plurality of vehicles 20 traveling within the tunnel T.

[0032] The control unit 120 executes overall control of the water leakage determination device 100. The control unit 120 is configured to include an image acquisition unit 121, an extraction unit 122, a temperature detection unit 123, a determination unit 124, and a machine learning unit 125.

[0033] The image acquisition unit 121 acquires temperature distribution images in the tunnel T over time, which are acquired by the vehicles 20 via the communication unit 110 and the network 300. Specifically, the image acquisition unit 121 acquires a plurality of temperature distribution images of the wall surface W in the tunnel T, which are captured by the cameras 21 of the vehicles 20 traveling in the tunnel T. The acquired temperature distribution images are stored in the storage unit 140 in association with the acquired position information.

[0034] The extraction unit 122 extracts a temperature change region where a temperature change has occurred from the temperature distribution image acquired by the image acquisition unit 121. Specifically, the extraction unit 122 extracts a temperature change region from within the temperature distribution image from temperature distribution images taken at the same position and at different times.

[0035] A method for extracting a temperature change region will be described with reference to Fig. 7. Fig. 7(a) and Fig. 7(b) show images of the inside of tunnel T captured by vehicle 20 at the same position at different times. Specifically, both of the views shown in Fig. 7(a) and Fig. 7(b) are examples of temperature distribution images obtained by extracting a portion of an image of wall surface W captured by vehicle 20 at the same position, and Fig. 7(b) is an image captured at time t2, which was captured after time t1 when Fig. 7(a) was captured.

[0036] The temperature detection unit 123 detects the temperature of the extracted temperature change region by comparing the temperature distribution images. Specifically, when the temperature distribution images are compared, three regions are included: region A where no temperature change occurs, a first temperature rise region B where a slight temperature rise occurs, and a second temperature rise region C where a significant temperature rise occurs. The temperature detection unit 123 detects the temperature difference value of the first temperature rise region B and the temperature difference value of the second temperature rise region C. The extraction unit 122 extracts the first temperature rise region B and the second temperature rise region C as a first step for determining whether or not the temperature rise is due to heat generation by the heat-generating material 10.

[0037] The determination unit 124 determines whether or not the cause of the temperature rise is due to water leakage, for the first temperature rise region B and the second temperature rise region C extracted by the extraction unit 122. Here, the cause of the temperature rise on the wall surface of the tunnel T can be various factors other than the temperature rise due to the heat generating material 10, such as the influence of the outside air temperature, the rise in the internal temperature inside the tunnel T, or measurement error. Therefore, it is determined whether or not the cause of the temperature rise is due to the rise in the heat generating material 10 caused by water leakage. The determination by the determination unit 124 can be made based on artificial intelligence (AI), for example, a learning model installed in the machine learning unit 125.

[0038] The machine learning unit 125 generates a learning model that indicates a correlation (relationship) between the acquired temperature distribution image and the occurrence of water leakage. Specifically, the machine learning unit 125 generates a learning model that performs machine learning on the relationship between the image data of the temperature distribution image and the determination result of the occurrence of water leakage based on a plurality of temperature distribution images (teacher data) that are correctly determined to have water leakage among the temperature distribution images as shown in FIG. 7(b). The learning model generated by the machine learning unit 125 is stored in the storage unit 140.

[0039] Based on a learning model obtained as a result of machine learning, the determination unit 124 determines whether or not the temperature rise is due to a heat-generating material for the first temperature rise region B and the second temperature rise region C extracted by the extraction unit 122. This makes it possible to accurately determine the location of a water leak even in a complex temperature distribution image.

[0040] In addition, various methods other than image recognition by artificial intelligence can be considered for determining whether or not water is leaking. For example, a threshold value (first threshold value) may be set in advance, and the temperature detected by the temperature detection unit 123 may be compared with the first threshold value to determine whether or not the temperature rise in the temperature change area is due to heat generation by the heat generating material 10.

[0041] For example, if the temperature changes from 10°C to 60°C during the time lapse from t1 to t2 in the second temperature rise region C, the temperature change (difference value) is 50°C. Considering that tunnel T is subject to few external factors such as an increase in air temperature, it is reasonable to determine that the difference value of 50°C is mainly caused by the heat generating material 10. Also, the temperature increase in the heat generating material 10 is mainly caused by a chemical reaction between moisture and the heat generating body. Therefore, the determination unit 124 determines that a water leak has occurred when the difference value exceeds a first threshold value. The first threshold value is a value of about 50°C that indicates the temperature change of the heat generating material 10 itself.

[0042] In addition, it takes a certain amount of time for the temperature of the heat generating material 10 to continue to rise and reach the maximum temperature after the occurrence of the water leak. Therefore, even if the difference value of the heat generating material 10 does not reach the first threshold value, if it exceeds a second threshold value that is less than the first threshold value, it may be determined that a sign of water leakage has occurred. Note that the second threshold value is, for example, a value of about 25°C, which is half the first threshold value. In this way, by determining the sign of water leakage while the temperature is rising higher than the surroundings, it is possible to predict water leakage at an early stage.

[0043] The heat generating material 10 returns to its original temperature after a certain time has elapsed since the temperature began to rise. That is, the average heat generating period of the heat generating material 10 is about 10 hours, and the heat generating period of the heat generating material 10 is limited, and after the heat generating period has elapsed, the temperature returns to the same level as before the heat generation. Therefore, if an image of the area including the heat generating material 10 cannot be obtained during the heat generating period of the heat generating material 10, it may lead to overlooking the water leakage. In order to avoid such inconvenience, multiple heat generating materials are arranged based on the position where the water leakage may occur, and the heat generating period is extended, so that the effects of the water leakage are not overlooked.

[0044] FIG. 8(a) is a diagram showing an example of the arrangement of heat generating materials for extending the heat generating period. As shown in FIG. 8(a), a plurality of heat generating materials 10 are arranged based on the water leakage position P. Here, heat generating materials 10b, 10c, and 10d are arranged in this order along the direction away from the water leakage position P. That is, the plurality of heat generating materials 10 are arranged so that the direction in which heat generating materials 10b, 10c, and 10d are arranged is diagonally downward (the direction of the white arrow in the figure) so as to be offset from the up-down direction in which the water leakage advances. In other words, the joint L and the arrangement direction of the heat generating materials 10 form an acute angle.

[0045] Leaking water is transmitted from the leak occurrence position P to each heat generating material 10. Most of the leaking water itself flows downward along the joints, but some of it seeps into the surrounding area from the joints. This leaking water is less in volume and flows more slowly, so the effects of the leaking water are transmitted in sequence to heat generating material 10b, heat generating material 10c, and heat generating material 10, which are arranged diagonally away from the direction in which the joint L extends. For this reason, the heat generation start times are delayed in the order of heat generating material 10c, heat generating material 10d, and heat generating material 10d.

[0046] 8(b) is a graph showing the extended heat generation period. In the graph, the dashed line shows the temperature distribution of heat generation material 10b, the dashed line shows the temperature distribution of heat generation material 10c, and the dashed line shows the temperature distribution of heat generation material 10d. The heat generation period of heat generation material 10b is the period from t11 to t12, the heat generation period of heat generation material 10c is the period from t13 to t14, and the heat generation period of heat generation material 10d is the period from t15 to t16.

[0047] Here, the heat generation period of each heat generating material 10 is almost the same, but the timing of the start of heat generation is shifted sequentially, so the timing of the end of heat generation is shifted accordingly in the order of heat generating material 10b, heat generating material 10c, and heat generating material 10d. Therefore, when heat generating material 10b, heat generating material 10c, and heat generating material 10d are viewed as a whole, the heat generation period is the solid line portion corresponding to the period from t11 to t16, and the heat generation period is extended compared to a single heat generating material 10.

[0048] In this way, the more heat generating materials 10 are used in combination, the longer the heat generating period can be, and therefore the time period during which a temperature distribution image can be acquired is extended, making it possible to avoid overlooking a water leak. Note that, although an example in which three heat generating materials 10 are arranged in a separated state in a direction away from the water leak occurrence position P has been shown here, the number and positions at which the heat generating materials 10 are arranged are not particularly limited.

[0049] The display unit 130 sequentially displays temperature distribution images of the wall surface W in the tunnel T. The display unit 130 is a display of the water leakage determining device 100 that displays a temperature distribution image such as that shown in Fig. 7(a) or 7(b), for example.

[0050] The storage unit 140 stores the temperature distribution images acquired over time by the image acquisition unit 121, the temperatures of each region obtained from the temperature distribution images, etc. The storage unit 140 also stores position information indicating the position at which the temperature distribution image was acquired and time information indicating the time at which the temperature distribution image was acquired in association with the temperature distribution image. Furthermore, the storage unit 140 stores thresholds (first and second thresholds) and a learning model generated by the machine learning unit 125.

[0051] In this way, the water leakage determination device 100 has an image acquisition unit 121 that acquires, over time, a temperature distribution image showing the temperature distribution of an area including the heat generating material 10, an extraction unit 122 that extracts a temperature change area in the temperature distribution image where a temperature change has occurred, and a determination unit 124 that determines whether or not a temperature change in the temperature change area is due to heat generation by the heat generating material. This makes it possible to automatically determine whether or not a water leakage has occurred in a structure, making it possible to find a water leakage earlier than when an operator periodically visually checks for the presence or absence of a water leakage in the tunnel T.

[0052] In addition, since the temperature distribution image is acquired by the camera 21 mounted on a moving body, which is a vehicle 20 such as a train, continuous images of the inside of the structure can be acquired over time. Therefore, it is possible to easily acquire the difference values ​​of the temperature distribution image.

[0053] Moreover, by providing a machine learning unit 125 in the water leakage determination device 100 and determining whether or not a temperature rise in the temperature change region is due to heat generation by the heat-generating material using a learning model generated by the machine learning unit 125, it is possible to appropriately determine which of the temperature change regions is due to heat generation by the heat-generating material. Moreover, by providing a temperature detection unit 123 in the water leakage determination device 100 and comparing a difference value of the detected temperature in the temperature change region with a preset threshold value to determine whether or not a temperature rise in the temperature change region is due to heat generation by the heat-generating material, it is also possible to accurately determine which is due to heat generation by the heat-generating material.

[0054] 9 is a perspective view showing an example of an earth retaining wall 200 at a construction site. The earth retaining wall 200 is installed to protect the vertical excavation surface that appears when the ground G is excavated as is. The earth retaining wall 200 is composed of a plurality of pillars 201 extending in the vertical direction and arranged in the horizontal direction. The earth retaining wall 200 is provided with braced beams 202.

[0055] The spaces between the multiple pillars 201 are prone to discontinuity, and cracks are particularly likely to occur between the pillars 201. There is a concern that water leakage may occur between the pillars 201 due to the influence of groundwater or rainfall, which may affect the construction environment and the surrounding environment. Therefore, construction companies are required to find water leakage early and prevent it.

[0056] A sheet of heat generating material 10e extending horizontally is placed below the retaining wall 200, which is a position where water due to leakage may be easily found. The heat generating material 10e is placed so as to cover the gaps that occur between the pillars 201. As a result, even if water leakage occurs from any of the cracks formed between the pillars 201, moisture can come into contact with the heat generating material 10e, and heat is generated at any point in the heat generating material 10.

[0057] A camera (thermo camera) 21a is placed at the construction site, and the camera 21a acquires temperature distribution images over time that show the temperature distribution of an area including the heat generating material 10e.

[0058] 10 is a schematic diagram showing an example of a temperature distribution image displayed on the screen of an information processing device such as a personal computer arranged at a construction site. The temperature distribution images of the heat generating material 10e acquired over time by the camera 21a may be sequentially displayed on the display unit 130. When the temperature of the heat generating material 10e rises, it is displayed as a third temperature rise region D in the temperature distribution image on the display unit 130. This allows a worker to check the temperature distribution image displayed on the display unit 130 at the construction site and find the heat generating location.

[0059] FIG. 11 is a schematic diagram showing an example of application of the heat generating material 10f indoors. The heat generating material 10f can be placed indoors as well as in outdoor facilities. For example, a machine room in which precision machinery that is sensitive to moisture is placed and a library in which books that are damaged when wet are stored are prone to damage from water leakage. Therefore, as shown in FIG. 11, for example, the heat generating material 10f is placed so as to extend horizontally on a wall surface where water leakage may occur. A camera (thermo camera) 21b placed indoors constantly captures a temperature distribution image of the heat generating material 10f.

[0060] By disposing the heat generating material 10f on the wall surface inside the room, for example, if a crack occurs in the wall surface causing a water leak, the heat generating material 10f generates heat, causing a temperature change in the temperature distribution image acquired by the camera 21b. The worker can check the temperature distribution image displayed on the display unit 130 and find the location of the heat generation. Note that the heat generating material 10g may be disposed not only on the wall surface but also near a drain outlet into which water may flow due to a water leak.

[0061] In this manner, in the water leakage detection method of the embodiment, heat generating materials 10 (10e, 10f, 10g) that generate heat by reacting with moisture are placed in positions where water may be generated due to leakage, and temperature distribution images showing the temperature distribution in the area including the heat generating materials 10 are obtained over time and the temperature distribution images are displayed sequentially on the display unit. As a result, a phenomenon that is difficult to detect, such as water leakage in a structure, is visualized by the temperature distribution images using the heat generating materials, so that the occurrence of a water leakage can be detected early.

[0062] Although an embodiment of the present invention has been described in detail above with reference to the drawings, the specific configuration is not limited to this embodiment, and design changes that do not deviate from the gist of the present invention are included in the present invention.

[0063] For example, in the above embodiment, the camera 21 and the water leakage determination device 100 are described as separate components, but the camera 21 and the water leakage determination device 100 may be an integrated device. For example, each railroad car may have the water leakage determination device 100 equipped with the camera 21, and the water leakage determination may be performed on the railroad car side. For example, a worker may carry a thermal camera during visual inspection and perform the water leakage determination. [Explanation of symbols]

[0064] 10: Heat generating material 21: Camera 100: Water leak detection device 121: Image acquisition unit 122:Extraction part 123: Temperature detection unit 124: Judgment section 125: Machine Learning Department 130: Display section T: Tunnel

Claims

1. A water leakage detection method for determining whether or not a water leakage occurs in a structure, comprising: A placement step of placing a heat generating material that generates heat by reacting with moisture at a position where water leakage may occur; an image acquisition step of acquiring a temperature distribution image over time that shows a temperature distribution in an area including the heat generating material; and a display step of sequentially displaying the temperature distribution images on a display unit.

2. 2. The water leakage detection method according to claim 1, wherein in the arranging step, a plurality of the heat generating materials are arranged in a direction away from a position where the water leakage may occur.

3. A water leakage determination device for determining whether or not water leakage occurs in a structure, an image acquisition unit that is disposed at a position where water leakage may occur and that acquires, over time, a temperature distribution image showing the temperature distribution of an area including a heat generating material that generates heat by reacting with moisture; an extracting unit that extracts a temperature change area where a temperature change occurs from the temperature distribution image; a determination unit for determining whether or not a temperature change in the temperature change region is due to heat generation by the heat generating material.

4. The water leakage determination device according to claim 3, wherein the temperature distribution image acquired by the image acquisition unit is acquired by a thermo camera mounted on a moving body.

5. A machine learning unit is provided with a learning model generated based on a plurality of temperature distribution images and a determination result of whether or not water is leaking, 5. The water leakage detection device according to claim 3, wherein the determination unit uses the learning model to determine whether or not a temperature rise in the temperature change region is caused by heat generation by the heat-generating material.

6. a temperature detection unit for detecting the temperature of the temperature change area; The water leakage detection device according to claim 3 or 4, characterized in that the determination unit determines whether or not the temperature rise in the temperature change area is due to heat generation by the heat generating material by comparing the detected temperature of the temperature change area with a preset threshold value.

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