Buried environment classification map creation device, buried environment identification device, buried environment classification map creation method, buried environment identification method, and program

Abstract

To provide a burying environment classification map making device which allows a more accurate prediction of corrosion of a buried pipe.SOLUTION: A burying environment classification map (a second burying environment classification map making device 63) includes: a first soil specification unit 63a for specifying a groundwater penetrating soil as a soil which exhibits a high permeability for groundwater; and a second soil specification unit 63b for specifying a soil of the groundwater penetrating soil which is located within a predetermined distance from a water source including salt and has an altitude within a predetermined height as a highly corrosive soil which is highly corrosive to a pipe.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a buried environment classification map creating device, a buried environment identifying device, a buried environment classification map creating method, a buried environment identifying method, and a program. [Background technology]

[0002] Pipes such as water pipes are buried in the soil. The pipes corrode over a long period of use. Japanese Patent Laid-Open Publication No. 2007-107882 (Patent Document 1) discloses a method for predicting corrosion of buried pipes. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-107882 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present disclosure is to provide a buried environment classification map creation device, a buried environment identification device, a buried environment classification map creation method, a buried environment identification method, and a program that enable more accurate prediction of corrosion of buried pipes. [Means for solving the problem]

[0005] The buried environment classification map creation device of the present disclosure includes a first soil identification unit that identifies groundwater permeable soil, which is soil that easily allows groundwater to pass through, and a second soil identification unit that identifies, among the groundwater permeable soils, soil that is located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height, as highly corrosive soil that is highly corrosive to pipes.

[0006] The buried environment identification device of the present disclosure includes a buried pipe data reading unit that reads buried pipe data including the location of the buried pipe, and a buried environment identification unit that applies the buried pipe data to the buried environment classification map created by the buried environment classification map creation device of the present disclosure to identify the buried environment of the buried pipe.

[0007] The buried environment classification map creation method of the present disclosure includes a step of identifying groundwater permeable soil, which is soil that easily allows groundwater to pass through, and a step of identifying, among the groundwater permeable soils, soil that is located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height, as highly corrosive soil that is highly corrosive to pipes.

[0008] The buried environment identification method of the present disclosure includes a step of reading out buried pipe data including the location of the buried pipe, and a step of applying the buried pipe data to a buried environment classification map created by the buried environment classification map creation method of the present disclosure to identify the buried environment of the buried pipe.

[0009] The program of the present disclosure causes a processor to execute each step of the buried environment classification map creation method of the present disclosure.

[0010] The program of the present disclosure causes a processor to execute each step of the buried environment identification method of the present disclosure. [Effects of the Invention]

[0011] The buried environment classification map creation device, buried environment identification device, buried environment classification map creation method, buried environment identification method, and program disclosed herein enable more accurate prediction of buried pipe corrosion. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a schematic diagram illustrating a hardware configuration of a water leakage accident rate prediction device according to an embodiment. [Figure 2] 1 is a block diagram illustrating a functional configuration of a water leakage accident rate prediction device according to an embodiment. [Figure 3]FIG. 2 is a block diagram illustrating the functional configuration of a storage unit of the water leakage accident rate prediction device according to the embodiment. [Figure 4] FIG. 2 is a block diagram illustrating a functional configuration of a map database unit according to the embodiment. [Figure 5] FIG. 2 is a diagram illustrating an example of a pipeline map included in buried pipe data according to an embodiment. [Figure 6] 10 is a diagram illustrating an example of a data structure of buried pipe attribute data included in buried pipe data according to an embodiment. FIG. [Figure 7] FIG. 10 is a diagram showing the data structure of a nominal pipe thickness database section. [Figure 8] FIG. 10 is a diagram showing an example of a provisional buried environment classification map. [Figure 9] FIG. 1 shows a box plot depicting the relationship between burial environment and corrosion rate. [Figure 10] FIG. 10 is a diagram showing the correspondence between first ground information and buried environment. [Figure 11] FIG. 1 is a diagram showing a box plot illustrating the relationship between the resistivity of groundwater and the corrosion status of buried pipes. [Figure 12] FIG. 1 shows a box plot illustrating the relationship between groundwater resistivity in gravel soil and distance from the coastline. [Figure 13] This figure shows examples of soils that can be considered as gravelly soils and non-gravelly soils in the surface geological map (subdivision). [Figure 14] Figure 1 shows a box plot showing the relationship between groundwater resistivity and elevation in gravel-based soils located 5 km or less from the coastline. [Figure 15] FIG. 10 is a diagram showing an example of a buried environment classification map. [Figure 16] FIG. 2 is a diagram illustrating a data structure of preprocessed buried pipe data according to an embodiment. [Figure 17] FIG. 10 is a diagram illustrating an example of a water leakage accident rate prediction result according to the embodiment. [Figure 18] FIG. 10 is a diagram showing another example of a water leakage accident rate prediction result according to the embodiment. [Figure 19] FIG. 1 is a flowchart illustrating a buried environment classification map creation method according to an embodiment. [Figure 20] FIG. 10 is a flowchart showing a buried environment classification map creation step according to an embodiment. [Figure 21] FIG. 1 is a flowchart illustrating a method for calculating a water leakage accident rate according to an embodiment. [Figure 22] FIG. 10 is a flowchart showing steps for creating preprocessed buried pipe data according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, embodiments of the present disclosure will be described. Note that the same reference numerals are used to designate the same components, and the description thereof will not be repeated.

[0014] 1 to 3, a water leakage accident rate prediction device 1 according to an embodiment will be described as an example of a buried pipe corrosion prediction device. The buried pipe water leakage accident rate is an example of an index for predicting buried pipe corrosion.

[0015] <Hardware configuration>

[0016] 1, the hardware configuration of the water leakage accident rate prediction device 1 will be described. The water leakage accident rate prediction device 1 includes an input device 11, a processor 12, a memory 13, a display 14, a network controller 16, a storage medium drive 17, and a storage 19.

[0017] The input device 11 accepts various input operations and is, for example, a keyboard, a mouse, or a touch panel.

[0018] The display 14 displays information necessary for processing in the water leakage accident rate prediction device 1. The display 14 displays, for example, a water leakage accident rate prediction result 50 (see FIG. 17 or 18) described later. The display 14 is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electroluminescence) display.

[0019] The processor 12 executes a program described below to perform processing required to realize the functions of the water leakage accident rate prediction device 1. The processor 12 is configured by, for example, a CPU or a GPU.

[0020] The memory 13 provides a storage area for temporarily storing program code, work memory, etc. when the processor 12 executes a program. The memory 13 is, for example, a volatile memory device such as a DRAM (Dynamic Random Access Memory) or an SRAM (Static Random Access Memory).

[0021] The network controller 16 transmits and receives programs or data to and from an external device (not shown) via a communication network (not shown). For example, the network controller 16 transmits a water leakage accident rate prediction result 50 (see FIG. 17 or FIG. 18) to an external device via the communication network. The network controller 16 may also receive buried pipe data 30 (see FIGS. 3, 5, and 6) from a customer via the communication network. The network controller 16 supports any communication method, such as Ethernet (registered trademark), wireless LAN, or Bluetooth (registered trademark).

[0022] The storage medium drive 17 is a device that reads out programs or data stored in the storage medium 18. The storage medium drive 17 may also be a device that writes programs or data to the storage medium 18. The storage medium 18 is a non-transitory storage medium that stores programs or data in a non-volatile manner. The storage medium 18 is, for example, an optical storage medium such as an optical disk (e.g., a CD-ROM or a DVD-ROM), a semiconductor storage medium such as a flash memory or a USB memory, a magnetic storage medium such as a hard disk, a floppy disk (FD) or a storage tape, or a magneto-optical storage medium such as an MO (Magneto-Optical) disk.

[0023] The storage 19 is a nonvolatile memory device such as a hard disk or a solid-state drive (SSD). The storage 19 stores buried pipe data 30 (see FIGS. 5 and 6), ground information maps (first ground information map 34 and second ground information map 35 shown in FIG. 4), a provisional buried environment classification map 36 (see FIG. 8), a buried environment classification map 38 (see FIG. 15), nominal pipe thickness data 33 (see FIG. 7), preprocessed buried pipe data 40 (see FIG. 16), a water leakage accident rate prediction model 42 (see FIG. 3), water leakage accident rates of buried pipes, and programs executed by the processor 12. The programs include a buried environment classification map creation program 47 (see FIG. 3) and a water leakage accident rate prediction program 48 (see FIG. 3).

[0024] The buried environment classification map creation program 47 is a program for creating a buried environment classification map 38 (see FIG. 15) from publicly available ground information maps (the first ground information map 34 and the second ground information map 35 shown in FIG. 4). The water leakage accident rate prediction program 48 is a program for calculating the water leakage accident rate of buried pipes from the buried pipe data 30.

[0025] Programs for realizing the functions of the water leakage accident rate prediction device 1, such as the buried environment classification map creation program 47 and the water leakage accident rate prediction program 48, may be stored in a non-transitory storage medium 18, distributed, and installed in the storage 19. Programs for realizing the functions of the water leakage accident rate prediction device 1, such as the buried environment classification map creation program 47 and the water leakage accident rate prediction program 48, may be downloaded to the water leakage accident rate prediction device 1 via the Internet or an intranet.

[0026] In this embodiment, an example is shown in which a general-purpose computer (processor 12) executes a program to realize the functions of the water leakage accident rate prediction device 1. All or part of the functions of the water leakage accident rate prediction device 1 may be realized using an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0027] <Functional configuration>

[0028] 2 to 4, an example of the functional configuration of the water leakage accident rate prediction device 1 will be described. Referring to Fig. 2, the water leakage accident rate prediction device 1 includes a memory unit 20, a buried pipe data receiving unit 60, a buried environment classification map creating unit 61, a buried pipe data preprocessing unit 64, a water leakage accident rate calculation unit 66, and a water leakage accident rate prediction result output unit 67.

[0029] <Storage section 20>

[0030] The memory unit 20 is realized by a storage 19 (see FIG. 1) or a storage medium 18 (see FIG. 1). As shown in FIG. 3, the memory unit 20 includes a buried pipe data memory unit 21, a nominal pipe thickness database unit 22, a map database unit 23, a buried environment classification map memory unit 24, a preprocessed buried pipe data memory unit 25, a water leakage accident rate prediction model memory unit 26, a water leakage accident rate memory unit 27, and a program memory unit 28.

[0031] Referring to FIG. 3, buried pipe data storage unit 21 stores buried pipe data 30. Buried pipe data 30 is data on buried pipes received from customers. Buried pipes are, for example, water pipes. Buried pipes are buried in the soil. Buried pipe data 30 includes, for example, a pipeline map 31 (see FIG. 5) and buried pipe attribute data 32 (see FIG. 6).

[0032] 5, the pipeline map 31 includes the pipeline ID of the buried pipe and the buried location (position) of the pipe. In the pipeline map 31, the pipeline ID of the buried pipe and the buried location of the pipe are associated with each other, and the buried location of the pipe is displayed on the map for each pipeline ID of the buried pipe.

[0033] Referring to FIG. 6, the buried pipe attribute data 32 includes, for example, the pipeline ID, installation year, nominal diameter, joint type, pipe thickness type, and pipeline length of the buried pipe. In the buried pipe attribute data 32, the pipeline ID, installation year, nominal diameter, joint type, pipe thickness type, and pipeline length are associated with one another. The installation year of a buried pipe is the year in which the buried pipe was installed (buried). Examples of joint types include A-type, K-type, T-type, and NS-type. Examples of pipe thickness types include type 1, type 2, and type 3. The pipeline length is the length of the buried pipe.

[0034] Referring to Fig. 3, the nominal pipe thickness database unit 22 stores nominal pipe thickness data 33 (see Fig. 7). The nominal pipe thickness data 33 includes, for example, the year of pipe installation, nominal diameter, joint type, pipe thickness type, and nominal pipe thickness. In the nominal pipe thickness data 33, the year of pipe installation, nominal diameter, joint type, pipe thickness type, and nominal pipe thickness are associated with each other. The nominal pipe thickness of a pipe is the standard pipe thickness of the pipe.

[0035] 3 and 4, the map database unit 23 stores a first ground information map 34 and a second ground information map 35. The first ground information map 34 includes, for example, a surface geological map (major classification, minor classification) 34a and a topography classification map (major classification, minor classification) 34b. The surface geological map (major classification, minor classification) 34a and the topography classification map (major classification, minor classification) 34b are provided by public institutions such as the Ministry of Land, Infrastructure, Transport and Tourism and are publicly available. The second ground information map 35 includes, for example, a surface geological map (minor classification) 35a, a coastline map 35b, and an elevation map 35c. The surface geological map (minor classification) 35a, the coastline map 35b, and the elevation map 35c are provided by public institutions such as the Ministry of Land, Infrastructure, Transport and Tourism and are publicly available. The classification of the surface geological map (minor classification) 35a corresponds to the minor classification of the surface geological map (major classification, minor classification) 34a.

[0036] 3, a provisional buried environment classification map 36 (see FIG. 8) and a buried environment classification map 38 (see FIG. 15) are stored in the buried environment classification map storage unit 24. The buried environment classification map 38 is a map showing the locations of buried environments A, B, C, and D, for example.

[0037] Buried Environment AD is the classification of the soil in which pipes are buried. In the Tentative Buried Environment Classification Map 36 and the Buried Environment Classification Map 38, soil in which pipes are buried is classified into four burial environments (AD) based on soil type and soil resistivity. Buried Environment A refers to soil with a soil resistivity of less than 1500 Ω·cm or soil with corrosive properties equivalent to that of the soil for buried pipes. Buried Environment B refers to clay soil with a soil resistivity of 1500 Ω·cm or higher or soil with corrosive properties equivalent to that of the clay soil for buried pipes. Buried Environment C refers to silt soil with a soil resistivity of 1500 Ω·cm or higher or soil with corrosive properties equivalent to that of the silt soil for buried pipes. Buried Environment D refers to sand soil with a soil resistivity of 1500 Ω·cm or higher or soil with corrosive properties equivalent to that of the sand soil for buried pipes. Of the buried environments AD, the buried environment A is the most corrosive to buried pipes.

[0038] The soil in which pipes are buried is classified into four burial environments, AD, for the following two reasons. The first reason is that the inventors discovered a statistically significant correlation between the AD burial environment and the corrosion rate of pipes from survey data on the relationship between the soil in which pipes are buried and the corrosion status of the pipes at approximately 6,000 locations across Japan (see Figure 9). The second reason is that the number of survey data that fall into the four AD burial environments accounts for the majority (80% or more) of the total number of survey data.

[0039] 3 and 8, the provisional buried environment classification map 36 is created, for example, from the first ground information map 34. The inventors have discovered that, with regard to the corrosion of buried pipes, there is a statistically significant correlation between the combination of the classification on the surface geological map (major classification, minor classification) 34a and the classification on the topography classification map (major classification, minor classification) 34b (see FIG. 10) and the buried environment AD. As shown in FIG. 10, the soil in which the pipes are buried is classified into four buried environments AD by combining the classification on the surface geological map (major classification, minor classification) 34a and the classification on the topography classification map (major classification, minor classification) 34b. In this way, the provisional buried environment classification map 36 is created.

[0040] 3 and 15, the buried storage environment classification map 38 is created from the provisional buried storage environment classification map 36 and the second ground information map 35.

[0041] The inventor analyzed survey data from a local government with a coastline. The inventor found a statistically significant correlation between the resistivity of groundwater contained in the soil in which pipes are buried and the corrosion status of the pipes (see FIG. 11). Specifically, the inventor found that the lower the resistivity of the groundwater, the greater the corrosion depth of the pipes. In FIG. 11, a high degree of corrosion of a buried pipe indicates a corrosion depth of 2 mm or more, a medium degree of corrosion of a buried pipe indicates a corrosion depth of more than 0 mm but less than 2 mm, and a low degree of corrosion of a buried pipe indicates a corrosion depth of 0 mm.

[0042] Referring to Figure 12, the inventors have found that, based on the survey data of the local government, the resistivity of groundwater contained in soil that can be considered gravel-based soil in the surface geological map (subdivision) 35a (see Figure 4), the location of the pipe buried in that soil, and the coastline map 35b (see Figure 4), there is a statistically significant correlation between the resistivity of groundwater and the distance from the coastline to the buried pipe location in soil that can be considered gravel-based soil in the surface geological map (subdivision) 35a (see Figure 12). For example, the inventors have found that the resistivity of groundwater contained in gravel-based soil located less than 5 km from the coastline is statistically significantly lower than the resistivity of groundwater contained in gravel-based soil located more than 5 km from the coastline. The primary reason for this is thought to be that when the soil in which the pipe is buried can be considered gravel-based soil, the soil is more permeable to groundwater. The second reason is thought to be that the closer the soil in which the pipes are buried is to the coastline, the more strongly the groundwater contained in that soil is affected by the salt contained in seawater.

[0043] As shown in Figure 13, examples of soil that can be considered to be gravelly soil in the surface geological map (subdivision) 35a include sand, sand (dune sand), and gravel deposits in the surface geological map (subdivision) 35a. In contrast, examples of soil that can be considered to be non-gravelly soil in the surface geological map (subdivision) 35a include alternating layers of sandstone and shale, gravel, sand, and mud, granitic rock, and tuffaceous breccia in the surface geological map (subdivision) 35a.

[0044] The inventor further analyzed the survey data of the above-mentioned local government, specifically survey data on pipes buried in gravel-based soil less than 5 km from the coastline (hereinafter referred to as "near-coast survey data"). As shown in Figure 14, the inventors analyzed the resistivity of groundwater contained in soil that can be considered gravel-based soil in the surface geological map (subdivision) 35a (see Figure 4), the location of the pipe buried in that soil, and the elevation map 35c (see Figure 4). They found that the resistivity of groundwater at the pipe burial site was statistically significantly lower when the soil in which the pipe was buried could be considered gravel-based soil in the surface geological map (subdivision) 35a, the pipe burial site was less than 5 km from the coastline, and the soil elevation at the pipe burial site was less than 3 m. This is thought to be because the lower the elevation of the soil at the pipe burial site, the closer the groundwater is to the pipe.

[0045] Therefore, the provisional buried environment classification map 36 was revised based on the second ground information map 35 to create a buried environment classification map 38. Specifically, by referring to the provisional buried environment classification map 36 and the surface geological map (minor classification) 35a (see Figure 4), soil that is easily permeable to groundwater (groundwater-permeable soil) is identified from the provisional buried environment classification map 36. Groundwater-permeable soil is, for example, soil that can be considered as gravel-based soil in the surface geological map (minor classification) 35a, regardless of the combination of the classification on the surface geological map (major classification, minor classification) 34a and the classification on the topography classification map (major classification, minor classification) 34b (see Figure 10). By referring to the coastline map 35b and the elevation map 35c, highly corrosive soil located within a predetermined distance from a salty water source and at an elevation within a predetermined height is identified from the groundwater-permeable soil. Highly corrosive soil is, for example, groundwater permeable soil that is located 5 km or less from the coastline and at an altitude of 3 m or less. In the provisional buried environment classification map 36, highly corrosive soil is identified as buried environment A, which has the highest corrosiveness to pipes among buried environments AD, regardless of the buried environment in the provisional buried environment classification map 36. In this way, a buried environment classification map 38 is created.

[0046] 3 and 16, the preprocessed buried pipe data storage unit 25 stores preprocessed buried pipe data 40. The preprocessed buried pipe data 40 is obtained by processing the buried pipe data 30 (FIGS. 3, 5, and 6) by the buried pipe data preprocessing unit 64 (see FIG. 2). The preprocessed buried pipe data 40 includes, for example, the pipeline ID of the buried pipe, the buried environment in the buried environment classification map 38, the buried period, and the nominal pipe thickness. The buried period is the period during which the buried pipe has been buried.

[0047] 3, the water leakage accident rate prediction model storage unit 26 stores a plurality of different water leakage accident rate prediction models 42 corresponding to a plurality of buried environments. The water leakage accident rate prediction models 42 include, for example, a water leakage accident rate prediction model for buried environment A, a water leakage accident rate prediction model for buried environment B, a water leakage accident rate prediction model for buried environment C, and a water leakage accident rate prediction model for buried environment D. The plurality of water leakage accident rate prediction models 42 are not particularly limited, and may be, for example, the water leakage accident rate prediction model disclosed in Japanese Patent Laid-Open No. 2021-56224 or a water leakage accident rate estimation formula for buried pipes provided by the Japan Water Research Center, a public interest incorporated foundation.

[0048] The buried pipe leakage accident rate estimation formula provided by the Japan Water Research Center, a public interest incorporated foundation, is given by the following formula (1). y represents the pipe leakage accident rate (events / km / year), C1 represents a correction coefficient related to the pipe specifications, C2 represents a correction coefficient related to the pipe diameter, C3 represents a correction coefficient related to the ground conditions in which the pipe is buried, and f(T) represents the standard accident rate curve for each pipe type. f(T) is given by the following formula (2). T represents the length of time the pipe has been buried, and coefficients a and b represent coefficients for each pipe type that indicate the degree of increase in the leakage accident rate over time. y=C1·C2·C3·f(T) (1) f(T)=a T b (2)

[0049] 3, the water leakage accident rate storage unit 27 stores the water leakage accident rate of buried pipes calculated by the water leakage accident rate calculation unit 66 (see FIG. 2). As shown in FIG. 18, the water leakage accident rate of buried pipes is stored in the water leakage accident rate storage unit 27 in association with the pipeline ID of the buried pipe.

[0050] Referring to FIG. 3, the program storage unit 28 stores programs for realizing the functions of the water leakage accident rate prediction device 1 (for example, a buried environment classification map creation program 47 and a water leakage accident rate prediction program 48).

[0051] <Buried pipe data reception unit 60>

[0052] Referring to FIG. 2, buried pipe data receiving unit 60 receives buried pipe data 30 (see FIGS. 3, 5, and 6) from a customer. Buried pipe data 30 is stored in buried pipe data storage unit 21 (see FIG. 3). Buried pipe data 30 may be stored in storage medium 18 (see FIG. 1) provided by the customer. Buried pipe data 30 may be received from the customer via a communication network. Buried pipe data 30 may be stored in advance in storage 19 (see FIG. 1).

[0053] <Burial Environment Classification Map Creation Division 61>

[0054] The buried environment classification map creating section 61 includes a first buried environment classification map creating section 62 and a second buried environment classification map creating section 63.

[0055] The first buried environment classification map creation unit 62 creates a provisional buried environment classification map 36 (see FIGS. 3 and 8) from the first ground information map 34 (see FIG. 4). The first ground information map 34 includes, for example, a surface geological map (major classification, minor classification) 34a and a topography classification map (major classification, minor classification) 34b.

[0056] Specifically, the first burial environment classification map creation unit 62 reads out the first ground information map 34 from the map database unit 23. The first burial environment classification map creation unit 62 classifies the soil in which the pipe is buried into four burial environments A, B, C, and D by combining the classifications on the surface geological map (major classifications, minor classifications) 34a with the classifications on the topography classification map (major classifications, minor classifications) 34b. In this way, the first burial environment classification map creation unit 62 creates a provisional burial environment classification map 36. The first burial environment classification map creation unit 62 outputs the provisional burial environment classification map 36 to the burial environment classification map storage unit 24 (see FIG. 3).

[0057] The second burial environment classification map creation unit 63 creates a burial environment classification map 38 from the provisional burial environment classification map 36 and the second ground information map 35 (see FIG. 4). The second burial environment classification map creation unit 63 includes a first soil identification unit 63a and a second soil identification unit 63b. The second ground information map 35 includes, for example, a surface geological map (minor classification) 35a, a coastline map 35b, and an elevation map 35c.

[0058] Specifically, the first soil identifying unit 63a reads the provisional burial environment classification map 36 from the burial environment classification map storage unit 24, and also reads the surface geological map (minor classification) 35a (see FIG. 4) from the map database unit 23. The first soil identifying unit 63a identifies soil that allows groundwater to easily pass through (groundwater permeable soil) in the provisional burial environment classification map 36. Groundwater permeable soil is, for example, soil that can be considered as gravel-based soil in the surface geological map (minor classification) 35a in the provisional burial environment classification map 36.

[0059] The second soil identification unit 63b reads the coastline map 35b and the elevation map 35c from the map database unit 23. Among the groundwater permeable soils identified by the first soil identification unit 63a, the second soil identification unit 63b identifies highly corrosive soils that are located within a predetermined distance from a salty water source and at a predetermined elevation. For example, the second soil identification unit 63b identifies, among the groundwater permeable soils, soils that are 5 km or less from the coastline and at an elevation of 3 m or less as highly corrosive soils. The second soil identification unit 63b identifies the highly corrosive soil in the provisional burial environment classification map 36 as burial environment A, which has the highest corrosiveness to pipes among burial environments AD, regardless of the burial environment in the provisional burial environment classification map 36. In this way, the second burial environment classification map creation unit 63 creates the burial environment classification map 38. The second burial environment classification map creating section 63 outputs the burial environment classification map 38 to the burial environment classification map storage section 24 (see FIG. 3).

[0060] <Buried pipe data preprocessing unit 64>

[0061] 2, the buried pipe data preprocessing unit 64 creates preprocessed buried pipe data 40 (see FIG. 16) from buried pipe data 30 (see FIGS. 3, 5, and 6). The buried pipe data preprocessing unit 64 includes a buried pipe data reading unit 64a, a buried period calculation unit 64b, a nominal pipe thickness identification unit 64c, a buried environment identification unit 64d, and a preprocessed buried pipe data creation unit 64e.

[0062] Specifically, the buried pipe data reading unit 64a reads buried pipe data 30 from the buried pipe data storage unit 21 (see FIG. 3). The buried pipe data 30 includes, for example, a pipeline map 31 (see FIG. 5) and buried pipe attribute data 32 (see FIGS. 3 and 6).

[0063] The buried period calculation unit 64b calculates the buried period of the buried pipe for each pipeline ID. For example, when obtaining a prediction result of the buried pipe water leakage accident rate for the current year (the year in which the prediction of the buried pipe water leakage accident rate is executed), the buried period calculation unit 64b calculates the buried pipe's buried period (see FIG. 16) as the difference between the current year stored in the storage unit 20 and the year of laying of the buried pipe attribute data 32 (see FIG. 6). When obtaining a prediction result of the buried pipe water leakage accident rate for a future year, the buried period calculation unit 64b calculates the buried pipe's buried period (see FIG. 16) as the difference between the future year received by the input device 11 (see FIG. 1) and stored in the storage unit 20 and the year of laying of the buried pipe attribute data 32 (see FIG. 6).

[0064] The nominal pipe thickness identification unit 64c reads out the nominal pipe thickness data 33 (see FIG. 7) from the nominal pipe thickness database unit 22 (see FIG. 3). The nominal pipe thickness identification unit 64c refers to the buried pipe attribute data 32, such as the installation year, nominal diameter, joint type, and pipe thickness type (see FIG. 6), and the nominal pipe thickness data 33, to identify the nominal pipe thickness of the buried pipe for each pipeline ID.

[0065] The buried environment identification unit 64d reads out the buried environment classification map 38 (see FIG. 15) from the buried environment classification map storage unit 24 (see FIG. 3). The buried environment identification unit 64d refers to the pipeline map 31 and the buried environment classification map 38 to identify the buried environment of the buried pipe for each pipeline ID. The preprocessed buried pipe data creation unit 64e combines the buried period, nominal pipe thickness, and buried environment of the buried pipe obtained for each pipeline ID to create preprocessed buried pipe data 40 (see FIG. 16). The buried pipe data preprocessing unit 64 outputs the preprocessed buried pipe data 40 to the preprocessed buried pipe data storage unit 25 (see FIG. 3).

[0066] <Water leakage accident rate calculation department 66>

[0067] Referring to Figures 2 and 3, the water leakage accident rate calculation unit 66 applies the preprocessed buried pipe data 40 to one of a plurality of water leakage accident rate prediction models 42 stored in the water leakage accident rate prediction model memory unit 26, and calculates the water leakage accident rate of buried pipes for each pipeline ID.

[0068] Specifically, the water leakage accident rate calculation unit 66 reads the preprocessed buried pipe data 40 from the preprocessed buried pipe data storage unit 25. The water leakage accident rate calculation unit 66 reads the buried environment for each pipeline ID from the preprocessed buried pipe data 40. The water leakage accident rate calculation unit 66 reads the water leakage accident rate prediction model 42 for the read-out buried environment from the water leakage accident rate prediction model storage unit 26 (see FIG. 3 ), among the multiple water leakage accident rate prediction models 42 stored in the water leakage accident rate prediction model storage unit 26. The water leakage accident rate calculation unit 66 inputs the buried period and nominal pipe thickness for each pipeline ID into the read-out water leakage accident rate prediction model 42, and calculates the water leakage accident rate of buried pipes for each pipeline ID. The water leakage accident rate of buried pipes is the number of water leakage accidents from buried pipes per unit time (e.g., 1 year) and per unit distance (e.g., 1 km). The water leakage accident rate calculation unit 66 outputs the water leakage accident rate of the buried pipe for each pipe line ID to the water leakage accident rate storage unit 27 (see FIG. 3).

[0069] <Water leakage accident rate prediction result output section 67>

[0070] 2, a water leakage accident rate prediction result output unit 67 outputs a water leakage accident rate prediction result 50 of buried pipes to at least one of the display 14, the storage medium 18, or the storage 19 shown in Fig. 1. The water leakage accident rate prediction result 50 may be, for example, a water leakage accident rate prediction map 51 (see Fig. 17) or a water leakage accident rate prediction table 52 (see Fig. 18).

[0071] The water leakage accident rate prediction result output unit 67 reads out the pipeline map 31 (see FIG. 5) from the buried pipe data storage unit 21 (see FIG. 3). The water leakage accident rate prediction result output unit 67 reads out the pipeline ID and the water leakage accident rate of the buried pipe from the water leakage accident rate storage unit 27. The water leakage accident rate prediction result output unit 67 creates a water leakage accident rate prediction map 51 by reflecting the water leakage accident rate of the buried pipe for each pipeline ID in the pipeline map 31. In the water leakage accident rate prediction map 51, the location of the buried pipe and the probability of a water leakage accident are displayed on a map for each pipeline ID.

[0072] The water leakage accident rate prediction result output unit 67 associates the pipeline ID with the water leakage accident probability to create the water leakage accident rate prediction table 52. In the water leakage accident rate prediction table 52, the pipeline ID of the buried pipe is associated with the water leakage accident rate.

[0073] <How to create a buried environment classification map>

[0074] The buried environment classification map creating method of this embodiment will be described with reference to Figures 19 and 20. The buried environment classification map creating method of this embodiment is executed by the buried environment classification map creating unit 61 (see Figure 2). The buried environment classification map creating method of this embodiment includes a step of creating a provisional buried environment classification map 36 (step S1) and a step of creating a buried environment classification map (step S2).

[0075] The step of creating the provisional burial environment classification map 36 (step S1) is executed by the first burial environment classification map creating unit 62 (see FIG. 2). In step S1, the first burial environment classification map creating unit 62 creates the provisional burial environment classification map 36 (see FIGS. 3 and 8) from the first ground information map 34 (see FIG. 4). The first ground information map 34 includes, for example, a surface geological map (major classification, minor classification) 34a and a topography classification map (major classification, minor classification) 34b.

[0076] Specifically, the first burial environment classification map creating unit 62 reads out the first ground information map 34 from the map database unit 23. The first burial environment classification map creating unit 62 classifies the soil in which the pipe is buried into four burial environments A, B, C, and D by combining the classifications on the surface geological map (major classifications, minor classifications) 34a with the classifications on the topography classification map (major classifications, minor classifications) 34b. In this way, the first burial environment classification map creating unit 62 creates a provisional burial environment classification map 36. The first burial environment classification map creating unit 62 outputs the provisional burial environment classification map 36 to the burial environment classification map storage unit 24 (see FIG. 3). The provisional burial environment classification map 36 is stored in the burial environment classification map storage unit 24.

[0077] The step of creating the buried environment classification map 38 (step S2) is executed by the second buried environment classification map creating unit 63 (see FIG. 2). In step S2, the second buried environment classification map creating unit 63 creates the buried environment classification map 38 (see FIGS. 3 and 15) from the provisional buried environment classification map 36 and the second ground information map 35 (see FIG. 4). The second ground information map 35 includes, for example, a surface geological map (minor classification) 35a, a coastline map 35b, and an elevation map 35c.

[0078] As shown in FIG. 20, the step of creating a burial environment classification map (step S2) includes a first soil identification step (step S4). Specifically, the first soil identification unit 63a reads out the tentative burial environment classification map 36 from the burial environment classification map storage unit 24, and also reads out the surface geological map (minor classification) 35a (see FIG. 4) from the map database unit 23. The first soil identification unit 63a identifies soil that allows groundwater to easily pass through (groundwater permeable soil) in the tentative burial environment classification map 36. Groundwater permeable soil is, for example, soil that can be considered as gravel-based soil in the surface geological map (minor classification) 35a in the tentative burial environment classification map 36.

[0079] As shown in FIG. 20, the step of creating the burial environment classification map (step S2) further includes a second soil identification step (step S5). Specifically, the second soil identification unit 63b reads a coastline map 35b and an elevation map 35c from the map database unit 23. The second soil identification unit 63b identifies highly corrosive soils located within a predetermined distance from a salty water source and at a predetermined elevation among the groundwater permeable soils identified by the first soil identification unit 63a. For example, the second soil identification unit 63b identifies, as highly corrosive soils, soils located within a predetermined distance from a salty water source and at an elevation of 3 m or less among the groundwater permeable soils. The second soil identification unit 63b identifies, as highly corrosive soils, burial environment A, which has the highest corrosiveness to pipes among burial environments A and D, regardless of the burial environment in the tentative burial environment classification map 36. In this way, the second burial environment classification map creating section 63 creates the burial environment classification map 38.

[0080] The second burial environment classification map creating section 63 outputs the burial environment classification map to the burial environment classification map storage section 24 (see FIG. 3). The burial environment classification map is stored in the burial environment classification map storage section .

[0081] <Water leakage accident rate prediction method>

[0082] Referring to Figs. 21 and 22, a water leakage accident rate prediction method according to this embodiment will be described as an example of a method for predicting corrosion of buried pipes.

[0083] Referring to FIG. 21, the buried pipe data receiving unit 60 (see FIG. 2) receives buried pipe data 30 (see FIGS. 3, 5, and 6) from a customer (step S11). The buried pipe data receiving unit 60 outputs the buried pipe data 30 to the buried pipe data storage unit 21 (see FIG. 3). The buried pipe data 30 includes, for example, a pipeline map 31 (see FIG. 5) and buried pipe attribute data 32 (see FIG. 6). The buried pipe data 30 is stored in the buried pipe data storage unit 21 (see FIG. 3). The buried pipe data 30 may be stored in a storage medium 18 (see FIG. 1) provided by the customer. The buried pipe data 30 may be received from the customer via a communication network. The buried pipe data 30 may be stored in advance in the storage 19 (see FIG. 1).

[0084] Referring to Figures 21 and 22, the buried pipe data pre-processing unit 64 (see Figure 2) creates pre-processed buried pipe data 40 (see Figure 16) from the buried pipe data 30 (see Figures 3, 5 and 6) stored in the buried pipe data storage unit 21 (see Figure 3) (step S12).

[0085] 22, the buried pipe data reading unit 64a (see FIG. 2) reads buried pipe data 30 from the buried pipe data storage unit 21 (see FIG. 3) (step S21). The buried pipe data 30 includes, for example, a pipeline map 31 (see FIG. 5) and buried pipe attribute data 32 (see FIGS. 3 and 6).

[0086] 22, the buried period calculation unit 64b (see FIG. 2) calculates the buried period of the buried pipe for each pipeline ID (step S22). For example, when obtaining a prediction result of the buried pipe water leakage accident rate for the current year (the year in which the prediction of the buried pipe water leakage accident rate is executed), the buried period calculation unit 64b calculates the difference between the current year stored in the storage unit 20 and the year of laying of the buried pipe attribute data 32 (see FIG. 6) as the buried period of the buried pipe (see FIG. 16). When obtaining a prediction result of the buried pipe water leakage accident rate for a future year, the buried period calculation unit 64b calculates the difference between the future year received by the input device 11 (see FIG. 1) and stored in the storage unit 20 and the year of laying of the buried pipe attribute data 32 (see FIG. 6) as the buried period of the buried pipe (see FIG. 16).

[0087] 22, the nominal pipe thickness identification unit 64c (see FIG. 2) identifies the nominal pipe thickness of the buried pipe for each pipeline ID (step S23). Specifically, the nominal pipe thickness identification unit 64c reads out the nominal pipe thickness data 33 (see FIG. 7) from the nominal pipe thickness database unit 22 (see FIG. 3). The nominal pipe thickness identification unit 64c identifies the nominal pipe thickness of the buried pipe for each pipeline ID by referring to the year of installation, nominal diameter, joint type, and type of pipe thickness (see FIG. 6) of the buried pipe attribute data 32 and the nominal pipe thickness data 33.

[0088] 22, the buried environment identification unit 64d (see FIG. 2) identifies the buried environment of the buried pipe for each pipeline ID (step S24). Specifically, the buried environment identification unit 64d reads out the buried environment classification map 38 (see FIG. 15) from the buried environment classification map storage unit 24 (see FIG. 3). The buried environment identification unit 64d refers to the pipeline map 31 and the buried environment classification map 38 to identify the buried environment of the buried pipe for each pipeline ID.

[0089] 22, the preprocessed buried pipe data creation unit 64e (see FIG. 2) combines the buried pipe installation period, nominal pipe thickness, and buried installation environment of the buried pipe obtained for each pipeline ID to generate preprocessed buried pipe data 40 (see FIG. 16) (step S25). The buried pipe data preprocessing unit 64 outputs the preprocessed buried pipe data 40 to the preprocessed buried pipe data storage unit 25 (see FIG. 3). The preprocessed buried pipe data 40 is stored in the preprocessed buried pipe data storage unit 25.

[0090] 21, the water leakage accident rate calculation unit 66 (see FIG. 2) calculates the water leakage accident rate of buried pipes for each pipeline ID (step S13). Specifically, the water leakage accident rate calculation unit 66 reads out the preprocessed buried pipe data 40 from the preprocessed buried pipe data storage unit 25 (see FIG. 3). The water leakage accident rate calculation unit 66 reads out the buried environment for each pipeline ID from the preprocessed buried pipe data 40. The water leakage accident rate calculation unit 66 reads out the water leakage accident rate prediction model 42 for the read-out buried environment from the water leakage accident rate prediction model storage unit 26 (see FIG. 3), out of the multiple water leakage accident rate prediction models 42 stored in the water leakage accident rate prediction model storage unit 26.

[0091] The water leakage accident rate calculation unit 66 inputs the buried period and nominal pipe thickness of the buried pipe for each pipeline ID into the read water leakage accident rate prediction model 42, and calculates the water leakage accident rate of the buried pipe for each pipeline ID. The water leakage accident rate calculation unit 66 outputs the water leakage accident rate of the buried pipe for each pipeline ID to the water leakage accident rate storage unit 27 (see FIG. 3). As shown in FIG. 18, the water leakage accident rate of the buried pipe is stored in the water leakage accident rate storage unit 27 in association with the pipeline ID.

[0092] 21, the water leakage accident rate prediction result output unit 67 (see FIG. 2) outputs the water leakage accident rate prediction result 50 to at least one of the display 14, the storage medium 18, or the storage 19 shown in FIG. 1 (step S14). The water leakage accident rate prediction result 50 may be, for example, a water leakage accident rate prediction map 51 (see FIG. 17) or a water leakage accident rate prediction table 52 (see FIG. 18).

[0093] The water leakage accident rate prediction result output unit 67 reads out the pipeline map 31 (see FIG. 5) from the buried pipe data storage unit 21 (see FIG. 3). The water leakage accident rate prediction result output unit 67 reads out the pipeline ID and the water leakage accident rate of the buried pipe from the water leakage accident rate storage unit 27. The water leakage accident rate prediction result output unit 67 creates the water leakage accident rate prediction map 51 by reflecting the water leakage accident rate of the buried pipe for each pipeline ID in the pipeline map 31. The water leakage accident rate prediction result output unit 67 creates the water leakage accident rate prediction table 52 by associating the pipeline ID with the water leakage accident probability.

[0094] A buried environment classification map creation program 47 (see FIG. 3) causes the processor 12 (see FIG. 1) to execute the buried environment classification map creation method of this embodiment. A water leakage accident rate prediction program 48 (see FIG. 3) causes the processor 12 (see FIG. 1) to execute the water leakage accident rate prediction method of this embodiment. A computer-readable recording medium (a non-transitory computer-readable recording medium, for example, storage medium 18) of this embodiment may record programs such as the buried environment classification map creation program 47 and the water leakage accident rate prediction program 48.

[0095] In this embodiment, the groundwater permeable soil is not limited to soil that can be considered as gravel soil in the surface geological map (subclassification) 35a (see Figure 4). In this embodiment, the sea is assumed as the salty water source, but the salty water source may also be, for example, a salt lake. The distance of the second region from the coastline is not limited to 5 km or less. The altitude of the second region is not limited to 3 m or less.

[0096] The effects of the buried environment classification map creation device (second buried environment classification map creation unit 63), buried environment identification device (buried pipe data preprocessing unit 64), buried environment classification map creation method, buried environment identification method, and program of this embodiment will be described.

[0097] The buried environment classification map creation device (second buried environment classification map creation unit 63) of this embodiment includes a first soil identification unit 63a that identifies groundwater permeable soil, which is soil that easily allows groundwater to pass through, and a second soil identification unit 63b that identifies, among the groundwater permeable soils, soil that is located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height, as highly corrosive soil that is highly corrosive to pipes.

[0098] Therefore, highly corrosive soil can be more accurately identified. The buried environment classification map creating device of this embodiment enables more accurate prediction of corrosion of buried pipes.

[0099] The buried environment identification device (buried pipe data preprocessing unit 64) of this embodiment includes a buried pipe data reading unit 64a that reads buried pipe data 30 including the location of the buried pipe, and a buried environment identification unit 64d that applies the buried pipe data 30 to the buried environment classification map 38 created by the buried environment classification map creation device (second buried environment classification map creation unit 63) of this embodiment to identify the buried environment of the buried pipe.

[0100] Therefore, the buried environment of the buried pipe can be more accurately identified. The buried environment identifying device of this embodiment enables more accurate prediction of corrosion of the buried pipe.

[0101] The buried environment classification map creation method of this embodiment includes a step (step S4) of identifying groundwater permeable soil, which is soil that easily allows groundwater to pass through, and a step (step S5) of identifying, from the groundwater permeable soil, soil that is located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height, as highly corrosive soil that is highly corrosive to pipes.

[0102] Therefore, highly corrosive soil can be more accurately identified. According to the buried environment classification map creation method of this embodiment, more accurate prediction of corrosion of buried pipes becomes possible.

[0103] The buried environment identification method of this embodiment includes a step of reading out buried pipe data 30 including the location of the buried pipe (step S21), and a step of applying the buried pipe data 30 to the buried environment classification map 38 created by the buried environment classification map creation method of this embodiment to identify the buried environment of the buried pipe (step S24).

[0104] Therefore, the buried environment of the buried pipe can be more accurately identified. According to the buried environment identification method of this embodiment, it is possible to more accurately predict corrosion of the buried pipe.

[0105] The program of this embodiment causes a processor to execute each step of the buried environment classification map creation method of this embodiment.

[0106] Therefore, highly corrosive soil can be identified more accurately. According to the program of this embodiment, more accurate prediction of corrosion of buried pipes becomes possible.

[0107] The program of this embodiment causes a processor to execute each step of the buried environment identification method of this embodiment.

[0108] Therefore, the buried environment of the buried pipe can be more accurately identified. According to the program of this embodiment, more accurate prediction of corrosion of the buried pipe becomes possible.

[0109] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0110] 1 Water leakage accident rate prediction device, 11 Input device, 12 Processor, 13 Memory, 14 Display, 16 Network controller, 17 Storage medium drive, 18 Storage medium, 19 Storage, 20 Memory unit, 21 Buried pipe data memory unit, 22 Nominal pipe thickness database unit, 23 Map database unit, 24 Buried environment classification map memory unit, 25 Preprocessed buried pipe data memory unit, 26 Water leakage accident rate prediction model memory unit, 27 Water leakage accident rate memory unit, 28 Program memory unit, 30 Buried pipe data, 31 Pipe map, 32 Buried pipe attribute data, 33 Nominal pipe thickness data, 34 First ground information map, 34a Surface geological map (major classification, minor classification), 34b Topography classification map (major classification, minor classification), 35 Second ground information map, 35a Surface geological map (minor classification), 35b Coastline map, 35c Elevation map, 36 Provisional buried environment classification map, 38 Buried environment classification map, 40 Preprocessed buried pipe data, 42 Water leakage accident rate prediction model, 47 Buried environment classification map creation program, 48 Water leakage accident rate prediction program, 50 Water leakage accident rate prediction result, 51 Water leakage accident rate prediction map, 52 Water leakage accident rate prediction table, 60 Buried pipe data reception unit, 61 Buried environment classification map creation unit, 62 First buried environment classification map creation unit, 63 Second buried environment classification map creation unit, 63a First soil identification unit, 63b Second soil identification unit, 64 Buried pipe data preprocessing unit, 64a Buried pipe data reading unit, 64b Buried period calculation unit, 64c Nominal pipe thickness identification unit, 64d Buried environment identification unit, 64e Preprocessed buried pipe data creation unit, 66 Water leakage accident rate calculation unit, 67 Output section for water leakage accident rate prediction results.

Claims

1. a first soil identification unit that identifies groundwater permeable soil, which is soil that easily passes groundwater; A buried environment classification map creation device comprising a second soil identification unit that identifies, among the groundwater permeable soils, soil that is located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height as highly corrosive soil that is highly corrosive to pipes.

2. a buried pipe data reading unit that reads buried pipe data including the location of the buried pipe; A buried environment identification device comprising: a buried environment identification unit that applies the buried pipe data to a buried environment classification map created by the buried environment classification map creation device described in claim 1 to identify the buried environment of the buried pipe.

3. A buried environment classification map creation method executed by a processor, comprising: Identifying groundwater permeable soil, which is soil that easily passes groundwater; and identifying, among the groundwater-permeable soils, soils that are located within a predetermined distance from a salt-containing water source and at an altitude within a predetermined height as highly corrosive soils that are highly corrosive to pipes.

4. A buried environment identification method executed by a processor, comprising: Retrieving buried pipe data including the location of the buried pipe; A buried environment identification method comprising a step of applying the buried pipe data to a buried environment classification map created by the buried environment classification map creation method of claim 3 to identify the buried environment of the buried pipe.

5. A program that causes a processor to execute each step of the buried environment classification map creation method according to claim 3.

6. A program that causes a processor to execute each step of the buried environment identification method according to claim 4.

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