Water leak detection device, system, and method

Abstract

To provide a technique for detecting an underground water leak with higher accuracy.SOLUTION: A water leak detection device includes: an attenuation evaluation processing unit that inputs exploration data in which a received wave signal in which a reflected wave returned after radiating an electromagnetic wave into the ground is received, position information relating to a position at which the received wave signal is received, and a reflection time from when the electromagnetic wave is radiated until when the reflected wave is received, are associated with each other, and outputs attenuation evaluation data consisting of a plurality of attenuation evaluation values calculated by evaluating the attenuation of the reflected wave from the received wave signal of the exploration data, and a plurality of attenuation evaluation values in which the position information and the reflection time are associated with each other; and a leakage place detection processing unit that at least extracts attenuation evaluation data whose reflection times are close to each other within an arbitrary standard regarding the attenuation evaluation data output from the attenuation evaluation processing unit, and outputs leakage place detection data through a process of converting the attenuation evaluation data into a normalized and calculated relative value.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an apparatus, system, and method for detecting underground water leaks in water pipes using a ground-penetrating radar device. [Background technology]

[0002] As underground water pipes deteriorate, it is becoming increasingly important to conduct maintenance work to detect and repair underground leaks.

[0003] Patent Document 1 cites a method of detecting water leak sounds as a method for detecting water pipe leaks. However, manually determining the sound of water leaks using, for example, a listening rod requires skill. Also, electromagnetic wave exploration using ground penetrating radar (GPR) can be used to identify the buried location of water pipes. However, Patent Document 1 states that while exploration using ground penetrating radar can identify buried objects, cavities, etc., it cannot detect water leaks.

[0004] Patent Document 2 describes an underground exploration method for determining the underground situation by evaluating the occurrence rate of reflected wave signal strength values ​​received by an underground radar.

[0005] Non-Patent Document 1 states that when a steel pipe buried underground is detected using a ground-penetrating radar, the reflection position of the steel pipe becomes deeper as the groundwater level rises, making it possible to determine the volumetric water content and groundwater depth. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 9-196798 [Patent Document 2] Japanese Patent Application Laid-Open No. 2018-40615 [Non-patent literature]

[0007] [Non-Patent Document 1] Masaru Sakata, Toshimitsu Nozu, Keiji Tokutomi, Shingo Ogurabe, Toru Mino, "Estimation of Volumetric Water Content and Groundwater Depth Using Ground Penetrating Radar," Journal of the Society of Irrigation, Rural and Rural Engineering, Vol. 78, No. 4, 2010 Summary of the Invention [Problem to be solved by the invention]

[0008] However, when underground leaking water is mixed with the surrounding soil, it is difficult to see any difference in the degree of reflected wave signal intensity value, and therefore Patent Document 2 does not take into consideration the use of underground radar to detect underground leaking points.

[0009] Furthermore, the method described in Non-Patent Document 1 has the problem that it is not possible to estimate the volumetric water content or groundwater depth in the ground for buried pipes whose material and diameter do not show a strong reflection by ground penetrating radar, since the reflection position cannot be determined.

[0010] To know the underground conditions, a method of detecting them using a ground-penetrating radar is usually used. However, as described in Patent Document 1, there is a problem that even if a ground-penetrating radar is used, it is not possible to directly detect water leaks. Here, the underground radar image obtained using the underground radar will be described in detail below.

[0011] Figure 1 shows an example of an image of the survey data obtained by underground radar survey. An example of a radar device is one that a user pushes along the ground to perform a sweep survey. The radar moves along the sweep direction while emitting electromagnetic waves into the ground. Data on the reflected wave signals is acquired by continuously receiving the reflected waves while emitting the electromagnetic waves.

[0012] This radar device is not limited to a radar device that a user manually pushes to perform a sweep survey, but any radar device that can move along the ground may be used. For example, a radar device mounted on a vehicle or a radar device that can automatically move along the ground may be used. Note that while the survey is assumed to be conducted near buried water pipes, the extension direction of the buried pipes and the sweep direction above ground do not need to be parallel. Data acquisition in areas where no water pipes are buried underground is also anticipated.

[0013] Figure 1 is a schematic diagram of a radar image 10 of a buried water pipe with a small diameter and made of a material that is difficult to reflect radar, such as resin. The horizontal axis 11 represents the sweep direction of the ground-penetrating radar. The vertical axis 12 represents the reflection time, which is the time it takes for electromagnetic waves to be emitted into the ground and reflected and received. The reflection time is longer for reflected waves from objects deeper underground, so the vertical axis 12 corresponds to the direction of depth underground.

[0014] The radar image 10 is an image in which the received signal at each measurement position and reflection time corresponds to the brightness of the pixel. Here, the stronger the received signal, the greater the brightness, which is depicted as white in Figure 1. On the other hand, the weaker the received signal, the less brightness, which is depicted as black in Figure 1. The greater the black-and-white contrast, the stronger the reflection. Incidentally, ground surface reflection 13 is reflection from the ground surface.

[0015] The hollow dotted rectangle 14 indicates the buried location of the water pipe, but because the diameter of the water pipe is small and it is made of resin, no reflected image can be confirmed at the location of the hollow dotted rectangle 14. As a result, it is not possible to estimate the volumetric water content or groundwater depth underground. Furthermore, even if a ground-penetrating radar is used at a location where there is a water leak, the result obtained is similar to radar image 10, so the abnormality does not appear directly and cannot be detected.

[0016] Therefore, an object of the present invention is to provide a technology for detecting underground water leakage with higher accuracy using a ground penetrating radar. [Means for solving the problem]

[0017] A preferred aspect of the present invention is a water leak detection device comprising an attenuation evaluation processing unit that receives probe data as input and outputs attenuation evaluation data, and a water leak location detection processing unit that includes at least a horizontal comparison processing unit that outputs horizontal comparison data from the attenuation evaluation data output from the attenuation evaluation processing unit and outputs water leak location detection data. The probe data is data in which a received wave signal resulting from irradiating an electromagnetic wave into the ground and receiving a reflected wave that has returned is associated with position information regarding the position at which the received wave signal is received, and a reflection time from when the electromagnetic wave is irradiated until when the reflected wave is received. The attenuation evaluation data is data in which a plurality of attenuation evaluation values ​​are associated with the position information and the reflection time, and the attenuation evaluation value is a value calculated by defining an arbitrary range within the probe data and evaluating the attenuation of the reflected wave from the received wave signal by determining the difference between the maximum and minimum values ​​of the received wave intensity within that range, or the variance or standard deviation. The horizontal comparison data is data in which a plurality of horizontal comparison values, the position information, and the reflection time information are associated with each other, and the horizontal comparison values ​​are values ​​calculated by extracting and normalizing the attenuation evaluation data whose reflection times are close to each other within an arbitrary standard. The leak location detection data is the horizontal comparison data or data obtained by processing the horizontal comparison data.

[0018] Another preferred aspect of the present invention includes a step of evaluating attenuation of a reflected wave from a received wave signal of exploration data in which a received wave signal obtained by irradiating an electromagnetic wave into the ground and receiving a reflected wave that has returned, position information relating to a position at which the received wave signal was received, and a reflection time from when the electromagnetic wave was irradiated until when the reflected wave was received, are respectively associated with each other, and generating attenuation evaluation data in which a plurality of attenuation evaluation values, the position information, and information on the reflection time are respectively associated with each other; and generating horizontal comparison data in which a plurality of horizontal comparison values ​​calculated by extracting and normalizing attenuation evaluation data having reflection times that are close to a reference value and within the reference value are respectively associated with each other, the position information, and information on the reflection time. a step of dividing the horizontal comparison data into a plurality of areas, calculating an area evaluation value based on the horizontal comparison value calculated for each of the areas, and generating area evaluation data in which the plurality of area evaluation values, the position information, and the reflection time information are respectively associated with each other; a step of calculating a water leakage score value based on the water leakage location detection data, and generating water leakage score data in which the plurality of water leakage score values ​​are respectively associated with the position information; and a step of generating score determination data in which information determining the presence or absence of underground leakage at each point indicated by the position information is respectively associated with the position information based on the water leakage score data. [Effects of the Invention]

[0019] Even if it is not possible to directly determine whether a water leak has occurred from the underground radar image obtained using the underground radar, it is possible to detect the location of the underground water leak by evaluating the attenuation of the received signal. Also, even if it is not possible to determine the location of the reflection by the buried pipe, it is possible to detect the location of the water leak from the location where the signal is significantly attenuated. Furthermore, since underground water leaks can be determined automatically, it is possible to detect the location of underground water leaks without the need for advanced knowledge or expertise to analyze underground exploration data. Therefore, it is possible to provide a technology that detects underground water leaks with higher accuracy. [Brief explanation of the drawings]

[0020] [Figure 1] FIG. 1 is an image diagram showing an example of a radar image acquired by a ground-penetrating radar. [Figure 2] 1 is a diagram showing the overall configuration of a water leakage detection device in a first embodiment. [Figure 3] 2 is a diagram showing the configuration of a water leakage point detection processing unit of the water leakage detection device according to the first embodiment. FIG. [Figure 4A] FIG. 1 is a schematic diagram showing the correspondence when a strong received signal is represented as pixel brightness in a radar image. [Figure 4B] FIG. 1 is a schematic diagram showing the correspondence when a weak received signal is represented as pixel brightness in a radar image. [Figure 5] FIG. 2 is a schematic diagram showing pixel arrangement of the survey data. [Figure 6] FIG. 10 is a schematic diagram showing an arrangement of pixels of attenuation evaluation data. [Figure 7] FIG. 1 is a flow diagram showing a method for converting exploration data into attenuation assessment data. [Figure 8] 1 is a schematic diagram showing a group of horizontal pixels with the same reflection time; [Figure 9] FIG. 10 is an image diagram showing an image output of horizontal comparison data. [Figure 10] 1 is a diagram illustrating a computer system that is an example of a hardware configuration that can realize a water leakage detection device according to a first embodiment. [Figure 11] FIG. 10 is a diagram showing the configuration of a water leakage point detection processing unit of a water leakage detection device according to a second embodiment. [Figure 12] FIG. 10 is an image diagram showing the results of illustrating water leakage point detection data consisting of area evaluation values. [Figure 13] FIG. 10 is a diagram illustrating a computer system as an example of a hardware configuration that can realize a water leakage detection device according to a second embodiment. [Figure 14] FIG. 10 is a flow diagram showing the overall configuration of a water leakage detection device according to a third embodiment. [Figure 15] FIG. 10 is a diagram showing the configuration of a water leakage determination processing unit of a water leakage detection device according to a third embodiment. [Figure 16]FIG. 10 is an image diagram showing an outline of a method for calculating water leakage score data from area evaluation data. [Figure 17] FIG. 10 is a graph plotting the determined water leakage scores. [Figure 18] FIG. 10 is a diagram showing a computer system as an example of a hardware configuration that can realize a water leakage detection device according to a third embodiment. [Figure 19] 10 is a flow chart showing the configuration of a water leakage determination processing unit of a water leakage detection device according to a fourth embodiment. [Figure 20] FIG. 10 is a diagram showing a computer system as an example of a hardware configuration that can realize a water leakage detection device according to a fourth embodiment. [Figure 21] FIG. 10 is a flow diagram showing the overall configuration of a water leakage detection device according to a fifth embodiment. [Figure 22] FIG. 10 is a schematic diagram showing an arrangement of areas in area evaluation data. [Figure 23] FIG. 10 is a diagram showing a computer system as an example of a hardware configuration that can realize a water leakage detection device according to a fifth embodiment. [Figure 24] FIG. 10 is a flow diagram showing the overall configuration of a water leakage detection system according to a sixth embodiment. [Figure 25] FIG. 11 is a flow chart showing the overall configuration of a water leakage detection method according to a seventh embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0021] An embodiment of the present invention will be described below with reference to the drawings. In all the drawings used to describe the embodiment, the same components are generally designated by the same reference numerals, and repeated explanations will be omitted where appropriate. It goes without saying that, in the following embodiment, the components (including element steps, etc.) are not necessarily essential unless otherwise specified or considered to be clearly essential in principle.

[0022] Furthermore, when it is said that "consists of A," "is made of A," "has A," or "includes A," it goes without saying that it does not exclude other elements, unless it is specifically stated that only that element is included. Similarly, in the following examples, when referring to the shape, positional relationship, etc. of components, it is intended to include things that are substantially similar or similar to that shape, etc., unless it is specifically stated or when it is clearly considered otherwise in principle. Before explaining the examples, an overview of the data surveyed by ground penetrating radar will be provided.

[0023] One example of an embodiment is a water leak detection device characterized by having an attenuation evaluation processing unit that inputs exploration data in which location information regarding the location at which an electromagnetic wave is irradiated into the ground and a reflected wave is received, the reflection time from the irradiation of the electromagnetic wave until the reflected wave is received, and information on the reflected wave intensity are each associated with each other, defines an arbitrary range within the exploration data, calculates an attenuation evaluation value by obtaining one or more indicators of the difference between the maximum and minimum values ​​of the received wave intensity within that range, variance, or standard deviation, and outputs attenuation evaluation data in which a plurality of attenuation evaluation values, the location information, and the reflection time are each associated with each other, and a water leak location detection processing unit that extracts at least attenuation evaluation data that are close in reflection time within an arbitrary standard from the attenuation evaluation data output from the attenuation evaluation processing unit, and outputs water leak location detection data through a process of converting the attenuation evaluation data output from the attenuation evaluation processing unit into a normalized relative value using the maximum and minimum values ​​obtained from the extracted attenuation evaluation data. [Example]

[0024] Fig. 2 is a diagram showing the overall configuration of a water leakage detection device 201 according to this embodiment. Fig. 3 is a diagram showing the configuration of a water leakage point detection processing unit S2501, which is an example of the water leakage point detection processing unit S25 in Fig. 2. First, the processing of the water leak detection device in FIG. 2 will be described.

[0025] The water leak detection device 201 receives the exploration data 22 as input and outputs the leak location detection data 2601. The exploration data 22 is data in which location information relating to the location at which an electromagnetic wave is emitted into the ground and a reflected wave is received, the reflection time from the emission of the electromagnetic wave until the reflected wave is received, and information on the intensity of the reflected wave are all associated with each other. The water leak detection device 201 has an attenuation evaluation processing unit S23 and a leak location detection processing unit S25, and receives the exploration data 22 as input and passes it to the attenuation evaluation processing unit S23. The attenuation evaluation processing unit S23 evaluates the attenuation of the received signal from the exploration data 22, converts it into attenuation evaluation data 24, and passes it to the leak location detection processing unit S25. The attenuation evaluation data 24 is data in which an attenuation evaluation value is calculated by defining an arbitrary range within the exploration data and finding one or more indices of the difference between the maximum and minimum values ​​of the received wave intensity within that range, the variance, and the standard deviation, and in which a plurality of attenuation evaluation values ​​are associated with each other. The leak point detection processing unit S25 receives the attenuation evaluation data 24 as input and outputs leak point detection data 2601. The leak point detection processing unit S25 extracts at least the attenuation evaluation data having a reflection time that is close to the attenuation evaluation data within an arbitrary standard, converts the horizontal comparison values ​​converted into relative values ​​normalized using the maximum and minimum values ​​obtained from the extracted attenuation evaluation data into horizontal comparison data in which the position information and the reflection time information are associated with each other, and outputs leak point detection data 2601.

[0026] Next, the configuration of the water leak point detection processing unit S2501 shown in FIG. 3 will be described.

[0027] The leak point detection processing unit S2501 has a horizontal comparison processing unit S251 that compares the attenuation evaluation data 24 in the horizontal direction and converts it into horizontal comparison data. The horizontal comparison data is data in which a plurality of horizontal comparison values ​​obtained by extracting attenuation evaluation data whose reflection times are close within an arbitrary standard and converting them into relative values ​​normalized using the maximum and minimum values ​​obtained from the extracted attenuation evaluation data are associated with the position information and the reflection time information. The leak point detection processing unit S2501 is an example of the leak point detection processing unit S25 in Figure 2, and here it is assumed that S2501 is the same as S251. Therefore, the horizontal comparison data that is the output of the horizontal comparison processing unit S251 shown in Figure 3 becomes the leak point detection data 2601, and corresponds to the output of the water leak detection device 201 shown in Figure 2.

[0028] The water leak detection device 201 shown in FIG. 2 receives underground radar detection data 22 and outputs leak location detection data 2601, highlighting underground leak locations for easier identification. The following describes the details of each processing unit shown in FIG. 2. The detection data 22 corresponds to measurement data acquired by the radar device. This detection data 22 also includes detection data extracted from data previously measured using an array-type underground radar device along an arbitrary line. The detection data 22 is data that associates location information regarding the location at which electromagnetic waves are emitted into the ground and the reflected waves are received, the reflection time from the emission of the electromagnetic waves to the reception of the reflected waves, and information on the intensity of the reflected waves. Note that the location information does not only include absolute locations such as coordinates in GPS (Global Positioning System) information, but also relative locations based on a certain location. For example, information such as the sweep distance and sweep direction from the start of the detection also corresponds to the location information. The radar image 10 shown in FIG. 1 is an example of the detection data 22 displayed as an image.

[0029] A method for converting the exploration data 22 into the attenuation evaluation data 24 in the attenuation evaluation processing unit S23 will be described with reference to FIGS. 4A and 4B. 4A and 4B are diagrams showing the correspondence between pixel brightness and received signals in radar image 10. The horizontal axis 31 represents the magnitude of the received signal, and the vertical axis 39 represents the reflection time from when the electromagnetic wave is emitted until it is received.

[0030] Received signal 33A shown in FIG. 4A and received signal 33B shown in FIG. 4B are signal waveforms obtained by irradiating electromagnetic waves underground and receiving reflected waves. Received signal 33A is a schematic representation of a strong reflected wave, i.e., a reflected wave with little attenuation. Received signal 33B is a schematic representation of a weak reflected wave, i.e., a reflected wave with large attenuation. Image pixel 34A and image pixel 34B are schematic diagrams showing received signals 33A and 33B as pixels of an underground radar image, with corresponding brightness. Here, areas with strong received signal strength are bright and shown in white, and areas with weak received signal strength are dark and shown in black. Received signal 33B has a smaller amplitude than received signal 33A. In this case, the brightness difference between each pixel is smaller for image pixel 34B than for image pixel 34A.

[0031] When the attenuation of the received signal is large, the amplitude becomes small, so attenuation can be evaluated by calculating the difference in brightness between pixels in a local area, as shown in image pixel 34A and image pixel 34B. Because the brightness of each pixel represents the magnitude of the received signal, attenuation can also be evaluated by calculating the difference in the measurement value of the received wave signal represented by each pixel instead of brightness. Hereinafter, the brightness corresponding to each pixel and the measurement value (intensity) of the received wave signal will be referred to as the "pixel value," and the set of pixel values ​​will be referred to as the "pixel data." The exploration data 22 is pixel data, and the attenuation evaluation processing unit S23 evaluates attenuation using the local pixel data and calculates the attenuation evaluation value.

[0032] The attenuation evaluation processing unit S23 will be described below. The attenuation evaluation processing unit S23 converts the detection data 22 into attenuation evaluation data 24. The attenuation evaluation data 24 is data having the same pixel arrangement as the detection data 22.

[0033] FIG. 5 is a schematic representation of a pixel group 41, which is a plurality of image pixels of the survey data 22. The x-axis represents the sweep direction of the ground-penetrating radar, and corresponds to position information relating to the position where the electromagnetic wave is emitted into the ground and the reflected wave is received. The y-axis corresponds to the reflection time from when the electromagnetic wave is emitted until it is received. Each pixel has position information on the x-axis and information on the received wave intensity corresponding to the reflection time on the y-axis. The x-axis and y-axis in FIGS. 6 and 8 are similar to those described above.

[0034] 6 shows a schematic diagram of the attenuation evaluation data 24, and pixel group 51 indicates the arrangement of data contained in the attenuation evaluation data 24 corresponding to pixel group 41 in FIG. 5. Here, a flow for calculating the attenuation evaluation value at the position of pixel 52 in the attenuation evaluation data 24 from the exploration data 22 will be described.

[0035] Fig. 7 shows the flow by which the attenuation evaluation processing unit S23 calculates the attenuation evaluation value. The attenuation evaluation value calculated in Fig. 7 becomes part of the attenuation evaluation data 24. In Fig. 7, the calculation range definition processing unit S61 extracts calculation range data 62, which is data used for calculation, from the exploration data 22 and passes it to the attenuation difference calculation processing unit S63. The attenuation difference calculation processing unit S63 converts the calculation range data 62 into a attenuation difference value 64 and passes it to the attenuation evaluation data creation processing unit S65. The attenuation evaluation data creation processing unit S65 converts it into a attenuation evaluation value using the attenuation difference value 64 and creates part of the attenuation evaluation data 24.

[0036] 6 for which the attenuation difference value 64 is to be calculated, and a thick-line frame 43 is defined with the pixel 42 at its center as shown in FIG. 5. The pixel 42 in the search data 22 is the pixel located at the same position as the pixel 52. The thick-line frame 43 indicates the calculation range data 62 used to calculate the attenuation difference value 64 corresponding to the pixel 52.

[0037] The vertical and horizontal widths of the thick-line frame 43 are assumed to be from one pixel to several hundred pixels and can be set arbitrarily. For example, the set range can be determined based on the wavelength of the electromagnetic waves used to acquire the data. Then, calculation range data 62 within the thick-line frame 43 is extracted.

[0038] The attenuation difference calculation processing unit S63 quantifies and indicates the magnitude of the change by calculating the difference between the maximum and minimum values ​​of the signal strength within the range of the calculation range data 62. Instead of the attenuation difference calculation processing unit S63, a value reflecting attenuation can also be calculated using a processing unit that calculates at least one of variance, standard deviation, etc. for the calculation range data 62. Alternatively, a plurality of calculation results may be integrated to calculate a value reflecting attenuation.

[0039] The attenuation evaluation data creation processing unit S65 stores the attenuation difference value 64 as a value corresponding to the position of the pixel 52 in the attenuation evaluation data 24.

[0040] Although the flow shown in FIG. 7 describes a method for calculating the value of the attenuation evaluation data 24 for pixel 52, the attenuation evaluation data 24 is generated by performing the same operation for all pixels in the pixel group 41.

[0041] The attenuation evaluation processing unit S23 has the effect of being able to find underground water leak points from the characteristics of the extracted attenuation evaluation data 24. In other words, it identifies the location where the signal attenuation is large, rather than the signal strength itself. Because water has the function of attenuating electromagnetic wave signals, it is possible to detect the location of the water leak point by detecting the location showing the attenuation characteristics from the attenuation evaluation data 24.

[0042] The horizontal comparison processing unit S251 included in the water leakage point detection processing unit S2501 shown in FIG. 3 normalizes the attenuation evaluation data 24 in the horizontal direction where the reflection time is the same. Figure 8 schematically illustrates the attenuation evaluation data 24, consisting of the attenuation evaluation values ​​obtained through the processing flow of Figure 7. A pixel group 71 represents the arrangement of data within a predetermined range of the attenuation evaluation data 24. In Figure 8, a bold-line frame 72 indicates pixels in the horizontal direction with the same reflection time. The attenuation evaluation values ​​within this bold-line frame 72 are normalized, with the maximum value as the upper limit and the minimum value as the lower limit. For example, normalization within a range of 0 to 10 is assumed. This process is performed sequentially for each row of the pixel group 71, resulting in the horizontal comparison data, which associates multiple horizontal comparison values, each normalized for the same reflection time, with the position information and the reflection time information. The normalization range can be set to an area with the same geological features, or, for example, every 15 meters, depending on the geological features and distance. Furthermore, in addition to using the maximum and minimum values ​​in each horizontal direction as the basis, a method of normalizing the data range, for example, approximately 3σ away from the average value, based on the standard deviation σ calculated from the attenuation evaluation data 24 in each horizontal direction, is also possible. Furthermore, although the bold frame 72 shown in Figure 8 is a range of only one pixel on the y-axis, it is also possible for the vertical width of the bold frame to be several pixels. In that case, the bold frame 72 indicates pixels in the horizontal direction with similar reflection times, and can be processed in the same way. The vertical width of the bold frame 72 can be set when extracting the attenuation evaluation data with similar reflection times within an arbitrary standard.

[0043] 9 is a schematic diagram showing a horizontal comparison data image 80, which is an image of the horizontal comparison data output by the horizontal comparison processing unit S251. The horizontal comparison data image 80 is an image in which each horizontal comparison value of the horizontal comparison data corresponds to the pixel brightness at each measurement position and reflection time. The horizontal axis 11 and the vertical axis 12 correspond to the horizontal axis 11 and the vertical axis 12 in FIG. 1. The ground surface reflection 83 corresponds to the ground surface reflection 13 in FIG. 1.

[0044] The black areas 81 are areas where the attenuation evaluation data 24 shows unique values ​​in the horizontal direction at the same reflection time, and correspond to underground water leaks. The attenuation evaluation processing unit S23 performs a calculation to compare brightness differences, for example, so it can distinguish between areas with low attenuation and areas with high attenuation, as shown in Figures 4A and 4B. When the brightness difference is calculated, the difference is smaller for image pixel 34B (Figure 4B) with high attenuation, so areas where attenuation occurs have a low attenuation evaluation value and are displayed with low brightness (black). However, since attenuation is small closer to the ground surface and large farther from the ground surface, performing a calculation to normalize in the horizontal direction makes attenuated areas stand out and emphasized, as shown in Figure 9. The horizontal comparison processing unit S251 converts the attenuation evaluation data 24 into the horizontal comparison data, which has the effect of making it easier to find areas of underground water leaks in particular. The attenuation of the reflected wave from the received wave signal is evaluated by calculating the difference, variance, or standard deviation between the maximum and minimum values ​​of the received wave intensity within a range such as the thick-line frame 43 within the exploration data, and the attenuation evaluation data 24 consisting of the calculated multiple attenuation evaluation values ​​is compared horizontally to highlight the difference between areas with and without leaks.

[0045] Signals from shallow underground parts have little attenuation, so the reflected wave intensity is large, and as shown in Figure 4A, the difference in reflected wave intensity appears large, and the absolute value of the attenuation evaluation value becomes large. On the other hand, signals from deep underground parts have little reflected wave intensity because they propagate over long distances, so the difference in reflected wave intensity appears small, and the absolute value of the attenuation evaluation value becomes small, as shown in Figure 4B. By normalizing and evaluating in the horizontal direction, the influence of the depth dependency of the attenuation evaluation value can be mitigated. Therefore, the location of underground water leakage that could not be displayed in the radar image 10 (Figure 1) can be identified in the horizontal comparison data image 80.

[0046] Therefore, the water leak detection device 201 has the effect of outputting the horizontal comparison data as water leak location detection data 2601 to identify underground water leak locations that cannot be identified using the input exploration data, thereby enabling identification using a horizontal comparison data image 80 that emphasizes the difference between locations with and without water leaks.

[0047] FIG. 10 shows a computer system PPA00, which is an example of a hardware configuration capable of realizing the water leak detection device 201 according to this embodiment. In the computer system PPA00, a processor PPP01 reads various programs stored in a memory resource PPA04 to perform various processes, including data generation, transmission, and reception, and the like. The processor PPP01 then executes the processes according to the programs. The computer system PPA00 is, for example, a personal computer, a tablet terminal, a smartphone, a server computer, a blade server, or a cloud server, and is a system that includes at least one of these computers. In other words, the computer system PPA00 also encompasses a system that includes, for example, a cloud server and a display computer (e.g., a tablet terminal or a smartphone). Another example of the computer system PPA00 is a controller that controls or manages some device, including the processor PPP01 and the memory resource PPA04.

[0048] Specifically, as shown in Fig. 10, the computer system PPA00 includes one or more processors PPP01, one or more memory resources PPA04, one or more UI (User Interface) devices PPP02, and one or more NI (Network Interface) devices PPP03. Note that the computer system PPA00 may include components other than these. The processor PPP01, UI device PPP02, NI device PPP03, and memory resource PPA04 are connected to one another via a bus PPP15.

[0049] The processor PPP01 is an arithmetic device that reads various programs stored in the memory resource PPA04 and executes processing corresponding to each program. Examples of such programs include an operating system (OS). The processor PPP01 may be a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), a field programmable gate array (FPGA), a quantum processor, or any other semiconductor device capable of executing calculations.

[0050] The memory resource PPA04 is a storage device that stores the attenuation evaluation program PPP05, the horizontal comparison program PPP06, the search data PPP10, the attenuation evaluation data PPP11, and the horizontal comparison data PPP12. Examples of the memory resource PPA04 include non-volatile memory and / or volatile memory. An example of the volatile memory is RAM (Random Access Memory). Examples of the non-volatile memory include rewritable storage media such as flash memory, hard disks, solid-state drives (SSDs), and read-only memories (ROMs), as well as USB (trademark) (Universal Serial Bus) memory, memory cards, and hard disks. RAMs such as magnetoresistive RAM (MRAM), phase-change RAM (PRAM), and resistive RAM (ReRAM) may also be considered non-volatile memory. The processor PPP01 may also provide a service for distributing various programs stored in the memory resource PPA04 to other computers.

[0051] The UI device PPP02 is an input device that inputs instructions from a user (or an operator) into the computer system PPA00, and an output device that outputs information generated by the computer system PPA00. Examples of input devices include a keyboard, a touch panel, a pointing device such as a mouse, and an audio input device such as a microphone. Unless otherwise specified below, input and output of information between the computer system PPA00 and the user is performed via the UI device PPP02. The UI device PPP02 may be only an input device or only an output device. Examples of output devices include display devices such as LCD displays, projectors that project information onto a screen, AR (virtual reality) glasses, printers that print on paper, smartphones, and smartwatches.

[0052] The NI device PPP03 is a communication device that communicates information with external devices. The NI device PPP03 communicates information with an underground radar device PPP17 and underground data PPP18, which stores survey data, via a predetermined communication network PPP16, such as the Internet or a local area network (LAN). The underground data PPP18 includes survey data previously measured by the underground radar, and is a data storage environment stored on a server that can be accessed online or in the cloud.

[0053] Unless otherwise specified below, information communication between the computer system PPA00 (or the processor PPP01) and an external device such as the underground radar device PPP17 is performed via the NI device PPP03.

[0054] This computer system PPA00 executes the processes of this embodiment by executing various programs PPP05 and PPP06.

[0055] The exploration data PPP10 is acquired from the underground radar device PPP17 and the underground data PPP18 via the NI device PPP03 and the bus PPP15.

[0056] The search data PPP10 can be input directly by the user from the UI device PPP02 or can be uploaded to the memory resource PPA04 via the bus PPP15.

[0057] The search data PPP10 corresponds to the search data 22, and indicates a state in which the search data 22 is stored in the memory resource PPA04.

[0058] The attenuation evaluation program PPP05 executes the processing of the attenuation evaluation processing unit S23. Similarly, the horizontal comparison program PPP06 executes the processing of the horizontal comparison processing unit S251. Furthermore, the attenuation evaluation data PPP11 is the attenuation evaluation data 24 stored in the memory resource PPA04, and the horizontal comparison data PPP12 is the horizontal comparison data output by the horizontal comparison program PPP06 stored in the memory resource PPA04. The water leak detection device 201 outputs the horizontal comparison data PPP12 generated by the computer system PPA00 to the user via the UI device PPP02 as leak location detection data 2601.

[0059] The UI device PPP02 can display, in diagrammatic form or as an image, not only the search data PPP10 that the computer system PPA00 has taken in, but also various data PPP11 and PPP12 that have been generated by executing various programs PPP05 and PPP06.

[0060] Therefore, the computer system shown in FIG. 10 has the advantage of being able to automatically execute the processing of the water leak detection device 201.

[0061] Instead of outputting to the user using the UI device PPP02 described above, data required for outputting to the user may be transmitted to an external processor system via the NI device PPP03. Examples of such data include the data to be output itself and data for generating output data in another processor system, but may also be a program or web data that describes the process of outputting to the user in the external processor system.

[0062] Instead of receiving input or operations from a user using the UI device PPP02 described above, data indicating user input or operations may be received from an external processor system via the NI device PPP03. From another perspective, the meaning of outputting data to a user may include not only the computer system PPA00 itself outputting the data, but also having another entity other than the computer system PPA00 output the data (using it). Furthermore, the meaning of receiving input or operations from a user may include not only direct output or reception to a user by the UI device PPP02 of the computer system PPA00, but also indirect reception by the computer system PPA00.

[0063] The effects described in this specification are merely examples and are not limiting, and other effects may be present. The present embodiment is not limited to the above-described embodiment and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to an embodiment including all of the components described. Furthermore, part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment can be added, deleted, or replaced with other configurations.

[0064] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. Furthermore, the above-described configurations, functions, etc. may be implemented in software by a processor interpreting and executing a program that implements each function. Information such as the program, decision table, and files that implement each function can be stored in memory, a storage device such as an HDD or SSD, or a recording medium such as an IC (Integrated Circuit) card, an SD (Secure Digital) card, or a DVD (Digital Versatile Disc). Furthermore, the control lines and information lines shown are those considered necessary for explanation, and do not necessarily represent all control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected. [Example]

[0065] In the second embodiment, a water leak detection device 202 will be described in which the water leak location detection processing unit S25 of the water leak detection device 201 of the first embodiment is replaced with a water leak location detection processing unit S2502 shown in FIG. 11. The water leak detection device 202 has a structure in which the water leak location detection processing unit S25 of the water leak detection device 201 shown in FIG. 2 is replaced with the water leak location detection processing unit S2502 shown in FIG. 11. In FIG. 11, compared to the first embodiment (FIG. 3), an area evaluation processing unit S252 is newly added to the water leak location detection processing unit S2502. In this embodiment, the horizontal comparison processing unit S251 passes the horizontal comparison data 25 to the area evaluation processing unit S252. The area evaluation processing unit S252 divides the horizontal comparison data 25 into a plurality of areas, calculates an area evaluation value for each area based on the horizontal comparison value, and generates area evaluation data consisting of the area evaluation values. The area evaluation data is data in which a plurality of area evaluation values ​​are associated with the position information and the reflection time information. The water leakage point detection processing unit S2502 outputs the area evaluation data as water leakage point detection data 2602.

[0066] The leak point detection processing unit S2502 receives the attenuation evaluation data 24 and outputs the leak point detection data 2602 calculated by the area evaluation processing unit S252. The leak detection device 202 receives the exploration data 22 and outputs the leak point detection data 2602.

[0067] The area evaluation value is calculated as the average value of the horizontal comparison data contained within each area. In addition to the average value, it is also possible to use statistical values ​​such as variance, standard deviation, and the difference between the maximum and minimum values. The size of the area can be set arbitrarily and is based on the wavelength of the electromagnetic waves to be irradiated and the resolution of the leak range to be determined. The set of divided area evaluation values ​​becomes the leak location detection data 2602.

[0068] 12 is a schematic diagram of an area evaluation data image 101, which is an image of the area evaluation data 28. The area evaluation data image 101 is an example of an image of the area evaluation data 28 in five levels. A rectangular frame 102 indicates the area size. The darker the area evaluation data image 101, the smaller the area evaluation value, which means that there is a greater possibility of underground water leakage.

[0069] The area evaluation processing unit S252 has the effect of being able to evaluate the overall presence or absence of water leakage in the observation target by dividing the horizontal comparison data 25 into multiple areas. The water leakage detection device 202 has the effect of being able to input the exploration data and output water leakage point detection data 2602 that can macroscopically evaluate areas where there is a high possibility of water leakage.

[0070] 13 shows a computer system PPB00, which is an example of a hardware configuration capable of realizing the water leak detection device 202 according to this embodiment. The memory resource PPB04 is a storage device that stores an attenuation evaluation program PPP05, a horizontal comparison program PPP06, an area evaluation program PPP07, exploration data PPP10, attenuation evaluation data PPP11, horizontal comparison data PPP12, and area evaluation data PPP13.

[0071] The computer system PPB00 shown in Fig. 13 has a configuration in which the memory resource PPA04 of the computer system PPA00 in Fig. 10 is replaced with the memory resource PPB04. The computer system PPB00 executes the processes of the water leakage detection device 202 by executing various programs PPP05 to PPP07.

[0072] The area evaluation program PPP07 performs processing in the area evaluation processing unit S252 using the horizontal comparison data PPP12. The area evaluation data PPP13 is the leak location detection data 2602 output by the area evaluation program PPP07 and stored in the memory resource PPB04. The water leak detection device 202 outputs the area evaluation data PPP13 generated by the computer system PPB00 to the user via the UI device PPP02.

[0073] The UI device PPP02 can display, in diagrammatic form and as an image, not only the probe data PPP10 imported by the computer system PPB00 but also various data PPP11 to PPP13 generated by executing various programs PPP05 to PPP07. Therefore, the computer system PPB00 shown in Fig. 13 has the effect of automatically executing the processing of the water leak detection device 202. [Example]

[0074] Fig. 14 is a diagram showing the overall configuration of the water leakage detection device 203 in Example 3. Fig. 15 is a diagram showing the configuration of a water leakage determination processing unit S2701, which is an example of the water leakage determination processing unit S27 in Fig. 14. First, the processing of the water leakage detection device in FIG. 14 will be described.

[0075] The water leakage detection device 203 in Fig. 14 is different from the water leakage detection device 201 in the first embodiment (Fig. 2) in that a water leakage determination processing unit S27 is newly added. The water leakage determination processing unit S27 performs processing to generate water leakage score data in which a plurality of water leakage score values ​​corresponding to each point are associated with the position information, based on at least the water leakage point detection data 26, and outputs water leakage determination data 2801. Note that the water leakage point detection processing unit S25 corresponds to either the water leakage point detection processing unit S2501 in the first embodiment (Fig. 3) or the water leakage point detection processing unit S2502 in the second embodiment (Fig. 11). In addition, the water leakage point detection data 26 corresponds to either the water leakage point detection data 2601 in the first embodiment (Fig. 3) or the water leakage point detection data 2602 in the second embodiment (Fig. 11). Next, the configuration of the water leakage determination processing unit S2701 shown in FIG. 15 will be described.

[0076] The water leakage determination processing unit S2701 has a water leakage score processing unit S271 that receives the water leakage point detection data 26 as input, calculates a water leakage score value at each point, and calculates water leakage score data consisting of a plurality of water leakage score values. The water leakage score data is data in which a plurality of water leakage score values ​​corresponding to each point indicated by the position information are associated with the position information, based on the water leakage point detection data. The water leakage determination processing unit S2701 is an example of the water leakage determination processing unit S27 in Fig. 14, and here, S2701 is assumed to be the same as S27. Therefore, the water leakage score data that is the output of the water leakage score processing unit S271 shown in Fig. 15 becomes water leakage determination data 2801, and corresponds to the output of the water leakage detection device 203 shown in Fig. 14.

[0077] The water leakage score data output by the water leakage score processing unit S271 is a set of data of water leakage score values ​​calculated at each data acquisition position, and the calculation method thereof will be described below.

[0078] Fig. 16 is an example of a water leakage point detection data image 126 obtained by imaging the water leakage point detection data 26. Here, the water leakage point detection data 26 is water leakage point detection data 2602 calculated based on the second embodiment. An outline of a method for calculating water leakage score data from the water leakage point detection data 26 will be described using Fig. 16.

[0079] The hollow rectangular frames 121 to 124 represent a vertical row of areas divided by the area evaluation processing unit S252, and the area evaluation value included in each frame is used to calculate the leakage score at the data acquisition position directly above.

[0080] The leakage score at each point is calculated by calculating the average of the area evaluation values ​​for the vertical column directly below it. In addition to the average, it can also be calculated by calculating statistical values ​​such as variance, standard deviation, and the difference between the maximum and minimum values.

[0081] Furthermore, with regard to the area evaluation values ​​for one vertical row used when calculating the leakage score, it is also possible to set a rule regarding the depth direction, such as using the area evaluation values ​​from the ground surface to a certain depth.

[0082] Figure 17 is a plot of the water leakage score data calculated using the above method. The vertical axis 130 indicates the water leakage score, and the horizontal axis 11 indicates the sweep direction. Water leakage score plot points 131 to 134 are plotted points of water leakage scores calculated using the evaluation values ​​of the areas within the hollow rectangular frames 121 to 124, and the same is true for the other plot points. For example, underground water leakage point 135 has a high water leakage score, indicating a high possibility of underground water leakage.

[0083] The water leakage score processing unit S271 has the effect of being able to quantitatively evaluate the possibility of underground leakage directly beneath each point. Therefore, the water leakage determination processing unit S2701 also has the effect of outputting the results of a quantitative evaluation of the possibility of water leakage for the water leakage point detection data. A location with a high possibility of underground leakage is easier to detect because the water leakage score shows a unique value compared to other locations.

[0084] 18 shows a computer system PPC00, which is an example of a hardware configuration capable of realizing the water leakage detection device 203 according to this embodiment. The memory resource PPC04 is a storage device that stores an attenuation evaluation program PPP05, a horizontal comparison program PPP06, an area evaluation program PPP07, a water leakage score calculation program PPP08, exploration data PPP10, attenuation evaluation data PPP11, horizontal comparison data PPP12, area evaluation data PPP13, and water leakage score data PPP14.

[0085] The computer system PPC00 shown in Fig. 18 has a configuration in which the memory resource PPB04 of the computer system PPB00 in Fig. 13 is replaced with the memory resource PPC04. The computer system PPC00 executes various programs PPP05 to PPP08 to perform the processing of the water leakage detection device 203 shown in the third embodiment (Fig. 14).

[0086] The water leakage score calculation program PPP08 performs processing in the water leakage score processing unit S271 using the area evaluation data PPP13. The water leakage score data PPP14 is the water leakage score data output by the water leakage score calculation program PPP08 and stored in the memory resource PPC04.

[0087] The UI device PPP02 can display, in diagrammatic form or as an image, not only the search data PPP10 captured by the computer system PPC00 but also various data PPP11 to PPP14 generated by executing various programs PPP05 to PPP08.

[0088] Therefore, the computer system shown in FIG. 18 has the effect of automatically executing the processing of the water leakage detection device 203 shown in the third embodiment. [Example]

[0089] In the fourth embodiment, a water leakage detection device 204 will be described in which the water leakage determination processing unit S27 of the water leakage detection device 203 of the third embodiment shown in Fig. 14 has been replaced with a water leakage determination processing unit S2702 shown in Fig. 19. The water leakage detection device 204 has a configuration in which the water leakage determination processing unit S27 of the water leakage detection device 203 shown in Fig. 14 has been replaced with a water leakage determination processing unit S2702 shown in Fig. 19. In Fig. 19, a score determination processing unit S272 is newly added to the water leakage determination processing unit S2702 compared to the third embodiment (Fig. 15). The water leakage score processing unit S271 passes the water leakage score data 27 to be output to the score determination processing unit S272. The score determination processing unit S272 determines the possibility of water leakage at a location corresponding to the data acquisition position from the water leakage score data 27, detects a location of underground water leakage, and outputs the data as water leakage determination data 2802. The water leakage determination processing unit S2702 receives the water leakage location detection data 26 as input, and generates score determination data in the score determination processing unit S272. The score determination data is data in which information determining the presence or absence of underground leakage at each point indicated by the location information is associated with the location information. The water leakage determination processing unit S2702 outputs the score determination data as water leakage determination data 2802.

[0090] The fourth embodiment has the effect of automatically determining the possibility of water leakage at each data acquisition position by inputting the underground radar exploration data.

[0091] The score determination processing unit S272 determines the presence or absence of underground leakage based on the amount of change in the leakage score data at each data acquisition location compared to a threshold or to previous or next points, and generates score determination data. For example, a method can be applied in which a certain threshold is set and a leakage possibility is determined when the threshold is exceeded. It is also possible to evaluate the possibility of leakage at each point in several stages by setting several thresholds and determining which threshold is exceeded. It is also conceivable to evaluate the leakage score value at the data acquisition location by comparing it with the leakage score value at surrounding locations. For example, the average leakage score value around the data acquisition location is calculated, and a score ratio, which is the ratio of the leakage score value to the average, is calculated. If the score ratio exceeds a certain value, it can be determined that there is a leakage possibility. It is also conceivable to evaluate the possibility of leakage in several stages by setting several evaluation standards for the score ratio and determining which standard the score ratio is exceeded.

[0092] The score determination processing unit S272 has the effect of being able to indicate the possibility of underground leakage based on the leakage score data. This allows the water leak detection device 204 to evaluate the attenuation of reflected waves from the exploration data 22 and output leakage determination data indicating the possibility of underground leakage, thereby enabling the determination of underground leakage. Furthermore, since underground leakage can be determined automatically, the measurer does not need to have advanced knowledge or expertise to analyze underground exploration data.

[0093] 20 shows a computer system PPD00, which is an example of a hardware configuration capable of realizing the water leakage detection device 204 according to this embodiment. The memory resource PPD04 is a storage device that stores an attenuation evaluation program PPP05, a horizontal comparison program PPP06, an area evaluation program PPP07, a water leakage score calculation program PPP08, a score determination program PPP09, exploration data PPP10, attenuation evaluation data PPP11, horizontal comparison data PPP12, area evaluation data PPP13, water leakage score data PPP14, and score determination data PPP19.

[0094] The computer system PPD00 shown in Fig. 20 has a configuration in which the memory resource PPD04 of the computer system PPC00 in Fig. 18 is replaced with the memory resource PPD04. The computer system PPD00 executes the processes of the water leakage detection device 204 by executing various programs PPP05 to PPP09.

[0095] The score determination program PPP09 performs the process of the score determination processing unit S272 using the water leakage score data PPP14. The score determination data PPP19 is the score determination data output by the score determination program PPP09 and stored in the memory resource PPD04.

[0096] The UI device PPP02 can display, in diagrammatic form or as an image, not only the search data PPP10 captured by the computer system PPD00, but also various data PPP11 to PPP14 and PPP19 generated by executing various programs PPP05 to PPP09.

[0097] Therefore, the computer system shown in FIG. 20 has the advantage of being able to automatically execute the processing of the water leak detection device 204. [Example]

[0098] In the fifth embodiment, a water leakage detection device 202A will be described in which the water leakage point detection processing unit S25 of the water leakage detection device 201 of the first embodiment (FIG. 2) is replaced with a water leakage point detection processing unit S2502A shown in FIG.

[0099] Fig. 21 shows a water leakage point detection processing unit S2502A of the water leakage detection device 202A. Compared to embodiment 1 (Fig. 3), Fig. 21 newly includes an area evaluation processing unit S252A. In this embodiment, the horizontal comparison processing unit S251 passes horizontal comparison data 25 to the area evaluation processing unit S252A. In addition, position information 36 regarding underground water leakage is provided as an input to the area evaluation processing unit S252A. The area evaluation processing unit S252A receives the position information 36 regarding underground water leakage as an input, sets the area evaluation value of the area specified by the position information regarding underground water leakage as a reference value, calculates secondary evaluation values ​​which are ratios of other area evaluation values ​​to the reference value, replaces the secondary evaluation value with the area evaluation value, and outputs area evaluation data in which information on the multiple replaced area evaluation values ​​is associated with the position information and the reflection time information. The water leak point detection processing unit S2502A receives the attenuation evaluation data 24 and the position information 36 regarding underground water leakage as input, and outputs the water leak point detection data 2602A calculated by the area evaluation processing unit S252A. The water leak detection device 202A receives the exploration data 22 and the position information 36 regarding underground water leakage as input, and outputs the water leak point detection data 2602A.

[0100] Location information 36 regarding underground leakage corresponds to information on the location of an underground leakage that has already been identified and information on a location that is known not to include an underground leakage. For example, if it is known from a buried water pipe installation drawing that there is no buried water pipe near a certain measurement point, there is no underground leakage at that point. Therefore, the location information of that measurement point can be included in location information 36 regarding underground leakage as information on a location where there is no underground leakage.

[0101] A method for converting the horizontal comparison data into leakage point detection data 2602A using the underground leakage position information 36 will be described below with reference to Fig. 22. It is assumed that the horizontal comparison data is calculated as described in the first embodiment.

[0102] FIG. 22 shows multiple area groups 19-20 in the area evaluation data 28. A rectangular box 102 represents one area. First, as in the first embodiment, the area evaluation processing unit S252A divides the horizontal comparison data into multiple areas and calculates area evaluation values. The calculated area evaluation value is called a primary evaluation value. Next, a reference area located directly below a point without water leakage is determined based on the underground leakage location information 36. Here, a dotted-line box 1921 represents the reference area. Next, a method for calculating a secondary evaluation value using the primary evaluation value included in the reference area will be described. Here, a method for calculating a secondary evaluation value corresponding to the area in the rectangular box 19212 will be described. First, a reference area is identified that is located at the same position on the vertical axis 12 as the area in the rectangular box 19212 and is within the reference area. Here, the area in the rectangular box 19211 corresponds to the reference area of ​​the rectangular box 19212. Next, the ratio of the primary evaluation value of the area in the rectangular box 19212 to the primary evaluation value of the reference area is calculated, and this is called the secondary evaluation value. In this manner, the secondary evaluation values ​​are calculated for the other areas as well, and then the area evaluation values ​​are replaced with the secondary evaluation values. The area evaluation processing unit S252A outputs area evaluation data in which the multiple area evaluation values ​​thus replaced, the position information, and the reflection time information are associated with each other as water leak location detection data 2602A.

[0103] By inputting the location information 36 related to underground leakage, the area evaluation processing unit S252A can use the underground exploration data of a location where there is definitely no leakage point or a location where there is a leakage point as a reference point to compare with other locations. Therefore, if location information related to underground leakage exists in advance, the location where underground leakage is occurring can be accurately identified by comparing with the reference point.

[0104] Furthermore, the water leakage score processing unit S271 of the third embodiment (FIG. 15) can also be adapted to input position information 36 regarding underground leakage and calculate water leakage score data using underground exploration data of locations where there is or is certainly no water leakage point as a reference. In this case, the water leakage score processing unit S271 of FIG. 14 calculates the water leakage score data from the water leakage point detection data 26 and the position information regarding underground leakage. Below, a method for converting the water leakage point detection data into the water leakage score data using the position information regarding underground leakage will be described. It is assumed that the water leakage point detection data is calculated as described in the second embodiment.

[0105] As shown in Example 3 (FIG. 16) in FIG. 16, the water leakage score value calculated from the area evaluation values ​​for one vertical column, as indicated by the hollow rectangular boxes 121 to 124, is the primary score value. Here, the primary score value at a location where it is known that there is no water leakage is the reference score value, and the ratio of the primary score value to the reference score value at each measurement point is the secondary score value. It is also possible that the water leakage score value is replaced with the secondary score value, and S271 outputs water leakage score data consisting of this replaced water leakage score value. By using underground exploration data from a location where there is definitely no water leakage point or a location where there is a water leakage point as the reference, the water leakage score processing unit S271 has the effect of outputting water leakage score data that accurately and quantitatively evaluates the possibility of water leakage from the water leakage point detection data.

[0106] FIG. 23 shows a computer system QQA00, which is an example of a hardware configuration capable of realizing the water leak detection device 202A according to this embodiment. Location information QQQ01 regarding underground water leakage is acquired via an NI device PPP03 and a bus PPP15. The NI device PPP03 communicates with an underground radar device PPP17 and an underground data PPP18, which stores survey data, via a communication network PPP16. The underground data PPP18 includes location information regarding underground water leakage in addition to the survey data. Location information regarding underground water leakage can also be acquired via the bus PPP15 by a user uploading input data to the UI device PPP02. Location information QQQ01 regarding underground water leakage is location information 36 regarding underground water leakage stored in the memory resource QQA02. The memory resource QQA02 is a storage device that stores the attenuation evaluation program PPP05, the horizontal comparison program PPP06, the area evaluation program QQQ07, the exploration data PPP10, the attenuation evaluation data PPP11, the horizontal comparison data PPP12, the area evaluation data QQQ13, and the location information QQQ01 regarding underground leakage.

[0107] The computer system QQA00 shown in Fig. 23 has a configuration in which the memory resource PPA04 of the computer system PPA00 in Fig. 10 is replaced with the memory resource QQA02. The computer system QQA00 executes various programs PPP05, PPP06, and QQQ07 to perform the processing of the water leak detection device 202A.

[0108] The area evaluation program QQQ07 performs processing in the area evaluation processing unit S252A using the position information QQQ01 regarding underground water leakage and the horizontal comparison data PPP12. The area evaluation data QQQ13 includes the area evaluation data 28 output by the area evaluation program QQQ07 and stored in the memory resource QQA02.

[0109] As described above, known information regarding the presence or absence of water leakage can be associated with location information and used as location information QQQ01 regarding underground water leakage, and the processor PPP01 calculates an area evaluation value using the location information QQQ01 regarding underground water leakage to obtain area evaluation data QQQ13.

[0110] The UI device PPP02 can display, in diagram form or image form, not only the search data PPP10 imported by the computer system QQA00, but also various data PPP11, PPP12, and QQQ13 generated by executing various programs PPP05, PPP06, and QQQ07.

[0111] Therefore, the computer system shown in FIG. 23 has the advantage of being able to automatically execute the processing of the water leakage detection device 202A. [Example]

[0112] 24 is a diagram showing the overall configuration of a water leak detection system 2000 in Example 6. The water leak detection system 2000 receives the exploration data 22 as input, and is composed of a water leak detection device 205, a display information extraction unit S29, and a display unit S31. The water leak detection device receives the exploration data 22 as input, and outputs water leak location detection data 26 and water leak determination data 2802. The display information extraction unit S29 generates display data 30 from the water leak location detection data 26 and the water leak determination data 2802, and the display unit S31 displays the display data 30.

[0113] The water leak detection device 205 is characterized in that it outputs new water leak location detection data 26 to the water leak detection device 203 of embodiment 3 (Fig. 14). The water leak detection device 205 receives the exploration data 22 as input and outputs the water leak location detection data 26 and water leak determination data 2802. Note that the water leak determination processing unit S27 shown in Fig. 24 corresponds to either the water leak determination processing unit S2701 of embodiment 3 (Fig. 15) or the water leak determination processing unit S2702 of embodiment 4 (Fig. 19).

[0114] The display information extraction unit S29 receives the water leakage determination data 2802 and the water leakage point detection data 26 as input, and outputs the display data 30.

[0115] The display information extraction unit S29 extracts water leak point detection data corresponding to points determined to have underground water leaks in the water leak determination data 2802 from the water leak point detection data 26. Then, information on the points determined to have underground water leaks and the extracted water leak point detection data are output as display data 30. Note that it is also possible to similarly extract water leak point detection data corresponding to points determined to have no underground water leaks in the water leak determination data 2802, and output information on the points determined to have no underground water leaks and the extracted water leak point detection data as display data 30.

[0116] The display information extraction unit S29 has the effect of showing the basis for the judgment by extracting and outputting the corresponding water leak detection data for points that have been judged by the water leak judgment processing unit S27 to have underground water leaks or to have a high possibility of underground water leaks.

[0117] In the water leak detection system, the display data 30 output by the display information extraction unit S29 is displayed on the display unit S31. The display unit S31 can display coordinate information or map location information for points determined to have a water leak on a display or on a web server. At the same time, it can also display an area evaluation data image such as that shown in Figure 12 corresponding to the points determined to have a water leak.

[0118] The water leak detection system 2000 can input the detection data 22 to display the location where underground water leakage is determined to exist, and can also present an area evaluation data image of the corresponding location. This has the effect of providing the user with a basis for knowing that there is a possibility of water leakage. In addition, displaying an area evaluation data image such as that shown in Figure 16 has the effect of making it easier for the user to determine how deep underground water leakage is occurring. [Example]

[0119] 25 is a flow diagram showing the steps of the water leak detection method for outputting the water leak determination data from the exploration data in the seventh embodiment. This corresponds to the processing steps from inputting the exploration data 22 to outputting the water leak determination data 2802 when the water leak detection device 204 in the fourth embodiment is used.

[0120] First, in the attenuation evaluation processing step S023, the attenuation of the reflected wave is evaluated from the exploration data in which a received wave signal that is a wave reflected back from an electromagnetic wave irradiated underground is associated with position information on the position at which the received wave signal was received, and a reflection time from when the electromagnetic wave was irradiated until the reflected wave is received, and attenuation evaluation data in which a plurality of attenuation evaluation values ​​are associated with the position information and information on the reflection time are generated. The attenuation evaluation processing step S023 corresponds to the processing step in which the attenuation evaluation processing unit S23 converts the exploration data 22 into attenuation evaluation data 24, as described in the first embodiment (FIG. 2).

[0121] In the horizontal comparison processing step S0251, the attenuation evaluation data having reflection times close to each other based on an arbitrary standard is extracted and normalized to generate horizontal comparison data in which a plurality of horizontal comparison values, the position information, and the reflection time information are associated with each other. The horizontal comparison processing step S0251 corresponds to the processing step in which the horizontal comparison processing unit S251 converts the attenuation evaluation data 24 into horizontal comparison data, as described in the first embodiment (FIG. 3).

[0122] In the area evaluation processing step S0252, the horizontal comparison data is divided into a plurality of areas, an area evaluation value is calculated based on the horizontal comparison value calculated for each of the areas, and area evaluation data in which the plurality of area evaluation values, the position information, and the reflection time information are associated with each other is generated as water leak point detection data. The area evaluation processing step S0252 corresponds to the processing step in which the area evaluation processing unit S252, described in the second embodiment (FIG. 11), calculates area evaluation data using horizontal comparison data as input, and outputs water leak point detection data 2602.

[0123] In the water leakage score processing step S0271, a water leakage score value at a point specified by the location information is calculated based on the water leakage point detection data, and water leakage score data is generated in which a plurality of water leakage score values ​​are associated with the location information. The water leakage score processing step S0271 is a step corresponding to the processing step in which the water leakage score processing unit S271 receives the water leakage point detection data 26 as an input and outputs the water leakage score data, as described in the third embodiment (FIG. 15).

[0124] In the score determination processing step S0272, the possibility of water leakage at the point specified by the location information is determined based on the water leakage score data, and score determination data in which information determining the presence or absence of underground water leakage at each point indicated by the location information is associated with the location information is generated as the water leakage determination data. The score determination processing step S0272 is a step corresponding to the processing step in which the score determination processing unit S272 described in Example 4 (FIG. 19) determines the possibility of water leakage from the water leakage score data, detects locations of underground water leakage, and outputs water leakage determination data 2802.

[0125] As described above, the flow of the water leak detection method for outputting the water leak determination data from the exploration data shown in Fig. 25 has the effect of converting the exploration data into water leak determination data and indicating the possibility of underground water leakage. Furthermore, even if you do not have advanced knowledge or expertise in analyzing underground exploration data, you can determine underground water leakage by performing each step shown in Fig. 25 in order. [Example]

[0126] The water leak detection method shown in the seventh embodiment can detect water leaks from plastic water pipes and water pipes with a diameter of approximately 50 mm or less.

[0127] Plastic water pipes include polyethylene pipes, hardened polyvinyl chloride pipes, impact-resistant hardened polyvinyl chloride pipes, heat-resistant hardened polyvinyl chloride pipes, and Elmex pipes. Buried pipes made of these materials usually do not reflect the electromagnetic waves emitted by ground-penetrating radar well, making them difficult to detect. Similarly, water pipes with a diameter of 50 mm or less, regardless of the material, are often below the resolution limit of ground-penetrating radar and are therefore difficult to detect.

[0128] Since the dielectric constants of the soil and the piping materials are different, electromagnetic waves are reflected at the boundary between them. s , the dielectric constant of the pipe is ε p When the magnetic permeability is equal, the reflection coefficient Γ when electromagnetic waves are incident perpendicularly from the soil onto the pipe is expressed as (Equation 1).

[0129]

number

[0130] The magnitude of the reflection coefficient Γ represents the ratio of the amplitude of the reflected wave to the amplitude of the incident wave, and if the pipe is a plastic pipe, it will be smaller than if it is a metal pipe, so the reflected image of the plastic pipe will not appear easily in the underground radar image.

[0131] Non-patent document 1 reports that when the moisture content of the ground increases at the leak point, the speed at which electromagnetic waves travel slows down, and the time it takes for the electromagnetic waves to be reflected from the buried pipe increases, causing the reflected image of the buried pipe to appear deeper in the radar image.

[0132] However, if the buried pipe is made of plastic, the reflection of the electromagnetic waves is weak, so the reflected image of the buried pipe may not be visible in the radar image. Also, if the diameter of the buried pipe is smaller than the wavelength of the electromagnetic waves, the reflected image of the buried pipe may not appear in the radar image. In such cases, since the reflected image of the buried pipe cannot be identified, it is not possible to determine from the radar image that the time between the emission of the electromagnetic waves and their reflection has become longer, making it impossible to determine whether there is an underground leak.

[0133] The water leak detection method shown in the seventh embodiment utilizes the fact that the reflected signal near the leak point is attenuated by water, and detects the leak point by evaluating this attenuation. Therefore, even if the reflected image of the buried pipe cannot be confirmed, it is possible to evaluate the possibility of a water leak by evaluating the attenuation of the reflected signal. [Explanation of symbols]

[0134] Leak detection device 201, exploration data 22, attenuation evaluation processing unit S23, attenuation evaluation data 24, leak point detection processing unit S2501, horizontal comparison processing S251, leak point detection data 2601

Claims

1. an attenuation evaluation processing unit that receives as input exploration data in which location information relating to a position at which an electromagnetic wave is irradiated underground and a reflected wave is received, a reflection time from the emission of the electromagnetic wave until the reflected wave is received, and information on the intensity of the reflected wave are all associated with each other, defines an arbitrary range within the exploration data, calculates an attenuation evaluation value by obtaining one or more indices of the difference between the maximum and minimum values ​​of the reflected wave intensity within that range, variance, and standard deviation, and outputs attenuation evaluation data in which a plurality of attenuation evaluation values, the location information, and the reflection time are all associated with each other; a leakage point detection processing unit that extracts at least the attenuation evaluation data output from the attenuation evaluation processing unit, each of which has a reflection time that is close to the other within an arbitrary standard, and converts the extracted attenuation evaluation data into a normalized relative value using the maximum and minimum values ​​obtained from the extracted attenuation evaluation data, thereby outputting leakage point detection data; A water leak detection device comprising:

2. The water leak detection device according to claim 1, The leak point detection processing unit extracts attenuation evaluation data having reflection times that are close to each other within an arbitrary standard, and outputs horizontal comparison data in which a plurality of horizontal comparison values ​​converted into relative values ​​normalized using maximum and minimum values ​​obtained from the extracted attenuation evaluation data, the position information, and the reflection time information are associated with each other. wherein the horizontal comparison data is the water leakage location detection data.

3. The water leakage detection device according to claim 2, The water leakage point detection processing unit further divides the horizontal comparison data into a plurality of areas, calculates an area evaluation value based on the horizontal comparison value calculated for each of the areas, and outputs area evaluation data in which the plurality of area evaluation values, the position information, and the reflection time information are associated with each other. wherein the area evaluation data is the water leakage location detection data.

4. The water leakage detection device according to claim 3, and a water leakage determination processing unit that outputs water leakage determination data through a process of calculating a plurality of water leakage score values ​​corresponding to each point indicated by the position information based on the water leakage point detection data. A water leak detection device comprising:

5. The water leakage detection device according to claim 4, The water leakage determination processing unit outputs water leakage score data in which a plurality of water leakage score values ​​corresponding to each point indicated by the position information are associated with the position information, based on the water leakage point detection data. wherein the water leakage determination data is the water leakage score data.

6. The water leakage detection device according to claim 5, The water leakage determination processing unit further outputs score determination data in which information determining the presence or absence of underground water leakage at each point indicated by the position information is associated with the position information based on the water leakage score data. wherein the score determination data is the water leakage determination data.

7. The water leakage detection device according to claim 6, By performing at least one of comparing the water leakage score value with a threshold value and comparing the water leakage score value with surrounding water leakage score values, it is determined whether or not there is underground water leakage at each point indicated by the location information. A water leak detection device characterized by:

8. The water leak detection device according to claim 1, The area evaluation unit of the leak point detection processing unit further receives position information regarding underground water leakage as an input, sets an area evaluation value of the area specified by the position information regarding underground water leakage as a reference value, calculates a secondary evaluation value which is a ratio of other area evaluation values ​​to the reference value, replaces the secondary evaluation value with the area evaluation value, and outputs area evaluation data in which the replaced multiple area evaluation values, the position information, and the reflection time are respectively associated with each other. wherein the area evaluation data is the water leakage location detection data.

9. A water leak detection system having a water leak detection device, a display information extraction unit, and a display unit, an attenuation evaluation processing unit that receives as input exploration data in which a reflected wave signal obtained by irradiating an electromagnetic wave underground and receiving a reflected wave that has returned, position information relating to the position at which the reflected wave signal was received, and a reflection time from when the electromagnetic wave was irradiated until when the reflected wave was received are all associated with each other, and outputs attenuation evaluation data in which a plurality of attenuation evaluation values ​​calculated by evaluating the attenuation of the reflected wave from the reflected wave signal of the exploration data are all associated with the position information and information on the reflection time; a horizontal comparison processing unit that extracts, from the attenuation evaluation data output from the attenuation evaluation processing unit, attenuation evaluation data having reflection times that are close within an arbitrary standard, normalizes and calculates a plurality of horizontal comparison values, and outputs horizontal comparison data in which the position information and the reflection time information are associated with each other, and outputs water leakage point detection data using the horizontal comparison data; a water leakage score processing unit that calculates a water leakage score value at a point specified by the position information based on the water leakage point detection data, and outputs water leakage score data in which a plurality of water leakage score values ​​and the position information are respectively associated, and outputs water leakage determination data using the water leakage score data; and the display information extraction unit outputs display data obtained by extracting water leakage point detection data and water leakage determination data corresponding to the point identified by the location information; The display unit displays the display data. A water leak detection system.

10. a step of evaluating the attenuation of the reflected wave from the reflected wave signal of the exploration data in which a reflected wave signal is received after irradiating an electromagnetic wave into the ground, position information relating to a position where the reflected wave signal is received, and a reflection time from when the electromagnetic wave is irradiated until when the reflected wave is received, are respectively associated with each other, and generating attenuation evaluation data in which a plurality of attenuation evaluation values ​​are respectively associated with the position information and information on the reflection time; generating horizontal comparison data in which a plurality of horizontal comparison values ​​calculated by extracting and normalizing the attenuation evaluation data having reflection times that are close to each other within a reference range are associated with the position information and the reflection time information; dividing the horizontal comparison data into a plurality of areas, calculating an area evaluation value based on the horizontal comparison value calculated for each of the areas, and generating area evaluation data in which the plurality of area evaluation values, the position information, and the reflection time information are associated with each other; calculating a water leakage score value based on the water leakage location detection data, and generating water leakage score data in which a plurality of water leakage score values ​​are associated with the location information; generating score determination data in which information determining the presence or absence of underground water leakage at each point indicated by the location information based on the water leakage score data is associated with the location information; A water leakage detection method comprising:

11. The water leakage detection method according to claim 10, The target for leak detection is leaks from plastic pipes or water pipes with a diameter of 50 mm or less. A water leak detection method characterized by:

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