CN115099998B

CN115099998B - Independent metering partitioning method, terminal equipment and storage medium of water supply network

Info

Publication number: CN115099998B
Application number: CN202210749841.7A
Authority: CN
Inventors: 邓立群; 詹益鸿; 辛萍; 何全泳; 陈成
Original assignee: Shenzhen Tuoan Trust Internet Of Things Co ltd
Current assignee: Shenzhen Tuoan Trust Internet Of Things Co ltd
Priority date: 2022-06-29
Filing date: 2022-06-29
Publication date: 2023-06-23
Anticipated expiration: 2042-06-29
Also published as: CN115099998A

Abstract

The application provides an independent metering partitioning method, terminal equipment and storage medium of a water supply network, which are applicable to the technical field of data processing, and the method comprises the following steps: the water supply network is divided into a plurality of primary partitions based on the natural boundary data. And screening out the target partition from the first-level partition. And clustering the nodes in the target partition, and dividing the target partition into a plurality of secondary partitions according to the clustering result. And taking the secondary partition and the primary partition which are not divided as independent metering partitions and monitoring to determine the partition to be updated. And if the partition to be updated is the secondary partition, the partition is carried out again on the target partition to which the partition to be updated belongs. According to the embodiment of the application, the cost of the independent metering partition of the water supply network in engineering application can be reduced.

Description

Independent metering partitioning method, terminal equipment and storage medium of water supply network

Technical Field

The application belongs to the technical field of data processing, and particularly relates to an independent metering and partitioning method, terminal equipment and storage medium of a water supply network.

Background

The water supply network is a water distribution network composed of water sources, water supply pipe sections, water demand nodes (hereinafter referred to as pipe sections and nodes) and the like, and is used for providing daily water for residents, industrial equipment, shared facilities and the like in the city. With the rapid development of economic and urban construction, a plurality of water supply networks are newly built and improved in China, and a plurality of pipe sections are replaced. However, due to pipe segment aging, joint leakage and other reasons, the water supply network still has serious leakage conditions. Therefore, how to reduce the leakage rate of the water supply network is an important problem to be solved in the water supply industry.

Independent metering partition (District Metering Area, DMA) management is to divide a municipal water supply network into a number of relatively closed independent metering areas, where each independent metering area is referred to as a DMA partition. By arranging a valve, a flowmeter and other devices on the boundary pipe section of the DMA partition, the monitoring and pressure regulation of the inlet flow and the outlet flow of the DMA partition can be realized. The leakage point position in the pipe network can be rapidly identified through DMA partition management, and the traditional passive leakage detection is changed into active leakage control, so that the method is an effective means for controlling leakage.

The conventional DMA partitioning method is an empirical partitioning, i.e. a technician determines which pipe sections are boundary pipe sections, which are valve ports for the boundary pipe sections, and which are required to install a flowmeter, etc., according to his own experience. Experience zoning is too dependent on the experience of the technician and has a large uncertainty. Meanwhile, the dimension often considered in partition is limited, so that the cost is too high in actual engineering popularization and application.

Disclosure of Invention

In view of this, the embodiments of the present application provide an independent metering and partitioning method, a terminal device, and a storage medium for a water supply network, which can solve the problem of higher engineering application cost existing in the independent metering and partitioning method for the water supply network.

A first aspect of an embodiment of the present application provides an independent metering and partitioning method for a water supply network, including:

natural boundary data of a region to be divided are obtained, and a water supply network of the region to be divided is divided into a plurality of first-level partitions based on the natural boundary data;

obtaining leakage data of each primary partition, and screening out a target partition from the primary partitions according to the leakage data;

calculating the node correlation between each node in the target partition based on the node characteristic data of each node in the target partition and the pipe section characteristic data of each pipe section;

according to the node correlation, carrying out clustering processing on the nodes in the target partition, and dividing the target partition into a plurality of secondary partitions according to a clustering result;

taking the second-level partition and the first-level partition which are not divided as independent metering partitions of a water supply network;

monitoring the independent metering partition, and determining a partition to be updated, wherein the partition to be updated is required to be updated;

and if the partition to be updated is a secondary partition, returning to execute the operation of dividing the target partition into a plurality of secondary partitions based on the node characteristic data of each node in the target partition and/or the pipe section characteristic data of each pipe section based on the target partition to which the partition to be updated belongs.

In a first possible implementation manner of the first aspect, after monitoring the independent metering partition and determining the partition to be updated in which the partition update is required, the method further includes:

and if the partition to be updated is an undivided primary partition, taking the partition to be updated as a target partition, and returning to execute the operation of dividing the target partition into a plurality of secondary partitions based on the node characteristic data of each node in the target partition and/or the pipe section characteristic data of each pipe section.

In a second possible implementation manner of the first aspect, clustering is performed on nodes in the target partition according to the node relevance, and the target partition is divided into a plurality of secondary partitions according to a clustering result, including:

according to the node relevance, carrying out multiple clustering treatment on the nodes in the target partition to obtain multiple clustering results, and determining partition dividing results corresponding to each clustering result; each partition division result comprises a plurality of secondary partitions;

comparing the partition division results, and screening out a partition division result with the least number of boundary pipe sections.

In a third possible implementation manner of the first aspect, calculating a node correlation between nodes in the target partition according to the node characteristic data and the pipe segment characteristic data includes:

And calculating a first correlation between each adjacent node in the target partition according to the pipe section characteristic data.

And calculating a second correlation degree between each adjacent node in the target partition according to the node characteristic data.

And calculating a third relativity between each adjacent node in the target partition according to the adjacent condition of each node in the target partition.

Node correlation between each adjacent node within the target partition is calculated based on the following formula:

wherein S is the node correlation degree of the node i and the node j, S1, S2 and S3 are the first correlation degree, the second phase Guan Du and the third correlation degree of the node i and the node j respectively, n is the total number of nodes in the target partition, max (sn) is the maximum value of the number of neighbor nodes of each node in the target partition, sn (i) and sn (j) are the number of neighbor nodes of the node i and the node j respectively, and the node i and the node j are any two adjacent nodes in the target partition.

With reference to the third possible implementation manner of the first aspect, as a fourth possible implementation manner of the first aspect, the pipe segment feature data includes: pipe inner diameter D, total flow Q1, night flow Q2, length L, pressure P and pipe friction loss coefficient H of the pipe section.

According to the pipe section characteristic data, calculating a first correlation between each adjacent node in the target partition, wherein the first correlation comprises the following steps: a first degree of correlation between each adjacent node within the target partition is calculated based on the following formula.

s1＝aD’+bQ1’+cQ2’+dL’+eP’+fH

Wherein s1 is a first correlation degree of the node i and the node j, D ', Q1', Q2', L ' and P ' are values after normalization processing of a pipe inner diameter D, a total flow Q1, a night flow Q2, a length L and a pressure P of a pipe section connecting the node i and the node j, H is a pipe section friction loss coefficient of the pipe section connecting the node i and the node j, a, b, c, D, e, f are preset weight coefficients, wherein values of a, D and f are larger than values of c, and values of c are larger than values of b and e.

With reference to the third possible implementation manner of the first aspect, as a fifth possible implementation manner of the first aspect, calculating, according to the adjacent condition of each node in the target partition, a third relatedness between each adjacent node in the target partition includes:

calculating a third correlation between each adjacent node in the target partition according to the following formula:

wherein s3 is a third correlation degree between the node i and the node j, and let the neighbor node shared by the node i and the node j be the node u, and sn (u) be the number of the node u.

With reference to the third possible implementation manner of the first aspect, as a sixth possible implementation manner of the first aspect, the node characteristic data includes: elevation, longitude, latitude, and water source of the node.

According to the node characteristic data, calculating a second correlation degree between each adjacent node in the target partition, including: based on the altitude, longitude and latitude, the spatial distance K between each adjacent node within the target zone is calculated.

And determining the water source correlation degree between each adjacent node in the target partition according to the water source.

Calculating a second degree of correlation between each adjacent node within the target partition based on the following formula:

wherein s2 is the second correlation degree of the node i and the node j, K' is the normalized value of the spatial distance K between the node i and the node j, W is the water source correlation degree between the node i and the node j, and g and h are preset weight coefficients.

On the basis of the fourth possible implementation manner of the first aspect, as a seventh possible implementation manner of the first aspect, the pipe segment friction loss coefficient of the pipe segment is determined according to the following formula:

h, L, V, C and D are the pipe section friction loss coefficient, length, water flow velocity in the pipe section, hazen-Williams coefficient and pipe inner diameter of the pipe section respectively.

In an eighth possible implementation manner of the first aspect, monitoring the independent metering partition, determining a partition to be updated in which a partition update is required includes:

and acquiring at least one index data of the number of users, the water quality condition, the leakage condition, the user complaint condition and the water difference degree between the independent metering partition and other independent metering partitions in the independent metering partition. And judging whether the independent metering partition is abnormal or not according to the acquired index data, and if so, judging that the independent metering partition is a partition to be updated which needs to be partitioned.

A second aspect of embodiments of the present application provides an independent metering and partitioning device for a water supply network, including:

the primary partition module is used for acquiring natural boundary data of the area to be partitioned and dividing the water supply network of the area to be partitioned into a plurality of primary partitions based on the natural boundary data.

The partition screening module is used for acquiring leakage data of each primary partition and screening target partitions from the primary partitions according to the leakage data.

And the correlation calculation module is used for calculating the correlation of the data.

The subdivision module is used for calculating the node correlation among the nodes in the target partition based on the node characteristic data of the nodes in the target partition and the pipe section characteristic data of the pipe sections; and carrying out clustering processing on the nodes in the target partition according to the node relevance, and dividing the target partition into a plurality of secondary partitions according to a clustering result.

The partition determining module is used for taking the secondary partition and the undivided primary partition as independent metering partitions of the water supply network.

And the partition monitoring module is used for monitoring the independent metering partition and determining the partition to be updated, which needs to be updated in the partition.

And the partition updating module is used for returning to execute the operation of dividing the target partition into a plurality of secondary partitions based on the node characteristic data of each node in the target partition and/or the pipe section characteristic data of each pipe section based on the target partition to which the partition to be updated belongs when the partition to be updated is the secondary partition.

A third aspect of the embodiments of the present application provides a terminal device, the terminal device including a memory, and a processor, where the memory stores a computer program executable on the processor, and when the processor executes the computer program, the processor causes the terminal device to implement the steps of the independent metering and partitioning method of the water supply network according to any one of the first aspect.

A fourth aspect of embodiments of the present application provides a computer-readable storage medium comprising: a computer program is stored which, when executed by a processor, causes a terminal device to carry out the steps of the independent metering and partitioning method of a water supply network as set forth in any one of the first aspects above.

A fifth aspect of the embodiments of the present application provides a computer program product, which when run on a terminal device, causes the terminal device to perform the independent metering and partitioning method of a water supply network according to any one of the first aspects above.

It will be appreciated that the advantages of the second to fifth aspects may be found in the relevant description of the first aspect, and are not described here again.

Compared with the prior art, the embodiment of the application has the beneficial effects that: on one hand, the embodiment of the application firstly performs primary partition on the water supply network based on the natural boundary (namely, the water supply network of the area to be partitioned is partitioned into a plurality of primary partitions based on the natural boundary data), and then performs secondary partition on the primary partition result (namely, the secondary partition is partitioned according to the characteristics of the nodes and the pipe sections), so that the partition of the DMA partition is more comprehensive and reasonable, the construction and management difficulty of the DMA partition is reduced, and the cost in engineering application is greatly reduced; on the other hand, a feedback regulation mechanism is introduced, when the secondary partition is unreasonable, the target partition to which the secondary partition belongs is divided again, so that the DMA partition can be updated and regulated according to actual application requirements under the framework of the original partition, the DMA partition is more reasonable, and the engineering change cost during updating is smaller, thereby greatly reducing the cost during engineering application.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of an independent metering and partitioning method of a water supply network according to an embodiment of the present disclosure;

fig. 2 is a schematic view of an application scenario provided in an embodiment of the present application;

fig. 3 is a schematic view of an application scenario provided in an embodiment of the present application;

FIG. 4 is a schematic flow chart of an independent metering and partitioning method of a water supply network according to an embodiment of the present disclosure;

fig. 5 is a schematic view of an application scenario provided in an embodiment of the present application;

FIG. 6 is a schematic flow chart of an independent metering and partitioning method of a water supply network according to an embodiment of the present disclosure;

fig. 7 is a schematic view of an application scenario provided in an embodiment of the present application;

FIG. 8 is a schematic flow chart of an independent metering and partitioning method of a water supply network according to an embodiment of the present disclosure;

FIG. 9 is a schematic structural diagram of an independent metering and partitioning device of a water supply network according to an embodiment of the present disclosure;

Fig. 10 is a schematic structural diagram of a terminal device provided in an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

The independent metering and partitioning method of the water supply network provided by the embodiment of the application can be applied to terminal equipment such as mobile phones, tablet computers and wearable equipment, and the terminal equipment is the execution main body of the independent metering and partitioning method of the water supply network provided by the embodiment of the application, and the embodiment of the application does not limit the specific type of the terminal equipment.

In practical application, due to the reasons of pipe segment aging, limited technical means investment, interface leakage and the like, the water supply pipe network generally has the situation of serious leakage. The leakage brings about not only waste of water resources but also waste of water treatment cost. DMA partition management is a very effective means to reduce leakage. However, the traditional experience partitioning method has the defects of relatively limited dimension consideration in partitioning the water supply network and incomplete consideration of the overall characteristic condition of the water supply network. Therefore, the final DMA partition scheme is high in engineering difficulty and cost when being popularized and applied practically, and is unfavorable for the popularization and application of the final DMA partition.

In the embodiment of the present application, an area that needs to be subjected to DMA partitioning is referred to as a to-be-partitioned area. In order to realize effective and reasonable partitioning of a water supply network in a region to be partitioned, the embodiment of the application firstly performs preliminary partitioning based on natural boundary data in the region to be partitioned to obtain a plurality of first-level partitions. On the basis, each primary partition is evaluated, the primary partition needing the fine partition is determined, and the characteristic data related to each node in the primary partition is acquired. And then, based on the characteristic data, carrying out secondary partition on the primary partition of the required partition to obtain a plurality of corresponding secondary partitions. And then obtaining a preliminary DMA partitioning result. And monitoring the preliminary DMA partition result, and updating the unmatched DMA partition in time when the preliminary DMA partition result is found to be unmatched with the actual water supply and management requirements.

According to the embodiment of the application, on one hand, the water supply network can be partitioned according to the characteristic data related to the natural boundary and the nodes. The pipe segment repartition aiming at the natural boundary is avoided, and meanwhile, the characteristic data related to the actual comprehensive nodes are fully considered. Therefore, the embodiment of the application can realize reasonable DMA partition of the water supply network, and greatly reduce the cost of engineering application after the DMA partition. On the other hand, the embodiment of the application can also realize monitoring feedback of the DMA partition result and self-adaptive adjustment of the DMA partition based on the feedback result. Therefore, the embodiment of the application can continuously and iteratively update the DMA partition to adapt to the requirements of actual water consumption and leakage management. Therefore, the DMA partition in the embodiment of the application is more reasonable and effective, and each iteration update is based on the adjustment of the last DMA partition result, so that the workload of engineering change is relatively less, and the cost requirement on engineering application is lower.

In order to illustrate the technical solutions described in the present application, the following description is made by specific examples.

Fig. 1 shows a flowchart of an implementation of an independent metering and partitioning method of a water supply network according to an embodiment of the present application, which is described in detail below:

s101, acquiring natural boundary data of a region to be divided, and dividing a water supply network of the region to be divided into a plurality of first-level partitions based on the natural boundary data.

The area to be divided needs to be determined according to the actual application condition. For example, in some alternative embodiments, the area to be divided may be an entire city, or may be a part of a city, such as a part of a city area of a city. In practice, some natural barriers or artificial barriers formed in urban construction are often included in cities. Such as natural rivers, mountains and lakes, artificially manufactured bridges, railways and arterial roads, etc. In the embodiments of the present application, these natural barriers and artificial barriers are collectively referred to as natural boundaries, and distribution data of these natural barriers and artificial barriers is referred to as natural boundary data.

In the course of urban development, the construction span of the water supply network is long, and many pipe sections are laid in a long history, for example, some pipe sections may be laid several decades ago. Because early water supply network planning tends to be older, these old pipe sections tend to be laid in combination with natural and artificial barriers in cities to reduce pipe section laying and management costs. Based on these actual pipe segment lay conditions, when DMA partitioning is performed, a single natural boundary is divided into multiple DMA partitions. In DMA partition management, it is necessary to install flowmeter, valve, etc. on pipe sections at these natural boundaries. It may even be necessary to repack some pipe sections for natural boundaries, such as to lay pipe sections across natural boundaries. However, in practical engineering application, the operations of installing equipment and laying pipe sections on natural boundaries are very difficult and the cost is very high. Meanwhile, the management difficulty of the DMA partition is greatly increased. Therefore, in the embodiment of the present application, the natural boundary data in the region to be divided is acquired first. Wherein natural boundary data may be pre-collected and stored by a technician without undue limitations herein.

On the basis of acquiring natural boundary data, the embodiment of the application can initially partition the water supply network in the area to be partitioned. In the embodiment of the present application, the basic principle of the preliminary partitioning is: the number of natural boundaries divided into the plurality of primary partitions cannot exceed the number threshold, or the ratio of the number of natural boundaries divided into the plurality of primary partitions to the total number of natural boundaries cannot exceed the ratio threshold. The number threshold and the ratio threshold may be set by a skilled person, and are not limited herein. On the basis of meeting the basic principle, the embodiment of the application does not excessively limit the specific method of the preliminary partition and can be set by a technician. For example, in some embodiments, a portion of the border segment may be determined following the trend of the natural border. The areas are closed by expanding and connecting adjacent boundary pipe sections, so that the preliminary division of DMA partitions is realized. Wherein the boundary pipe section refers to the pipe section of the outermost periphery of the DMA partition at the boundary. The operations of expanding and connecting the border segments may be regular or random, in case the natural border requirements are fulfilled.

As an alternative embodiment of the present application, on the basis of the natural boundary data, the first-level partition may be performed by referring to the administrative region partition data, the user distribution data, the user water use data, and the like in the region to be partitioned at the same time. At this time S101 may be replaced with: natural boundary data, administrative region division data, user distribution data and user water consumption data of the region to be divided are obtained, and the water supply network of the region to be divided is divided into a plurality of primary partitions based on the natural boundary data, the administrative region division data, the user distribution data and the user water consumption data.

When the data are divided by referring to the administrative regions, a single DMA partition can be avoided from crossing a plurality of administrative regions at the same time as much as possible, and the management cost is increased. Specifically, the technician may set the upper limit number of areas spanned by a specific primary partition across a plurality of administrative areas, and in the preliminary partition, the administrative area spanned by each primary partition does not exceed the upper limit number of areas. Meanwhile, in practical application, the number of users contained in a single DMA partition and the total water consumption of the users are not too large, and the management difficulty of the DMA partition is increased when the total water consumption of the users is too large, so that leakage analysis and management are not facilitated. Thus, in the embodiment of the present application, when a partition is divided, an upper limit of the number of users and an upper limit of the total water consumption of users contained in a single DMA partition may be set. When dividing a partition, the number of users (which may also be referred to as population size) contained in each partition is determined by the user distribution data, and the total water usage of the users contained in each partition is determined by the user water usage data. And if the upper limit of the number of users or the upper limit of the water consumption of the users is exceeded, the boundary pipe sections of the partition are selected again. And stopping preliminary division of the water supply network until the natural boundary division condition, administrative region crossing condition, user quantity condition and user water consumption condition in each partition meet the corresponding requirements, thereby obtaining a plurality of first-level partitions. The user water consumption data can be collected and stored in a manual meter reading mode and the like.

In the embodiment of the application, the natural boundary is taken as a primary partition reference basis, or the natural boundary, the administrative region, the number of users and the total water consumption of the users are taken as the primary partition reference basis, so that the conditions of the natural boundary and the like contained in a single primary partition can be controlled. So that management within a single primary partition is not too much hindered. In actual engineering, too many devices are not needed to be installed or too many pipe sections are not needed to be paved across natural boundaries, the existing pipe sections are fully utilized for valve and other device setting and leakage management, the cost of DMA partition management can be greatly reduced, and the engineering application cost is reduced.

By way of example, reference may be made to fig. 2, which is a schematic illustration of a water supply network to be divided into areas, which contains 39 nodes in total. After natural boundary data, administrative region division data, user distribution data, and user water consumption data are acquired, region division is performed according to the above requirements for the respective data. Referring to fig. 3, the water supply network may be divided into 3 primary partitions, namely primary partition 1, primary partition 2 and primary partition 3.

S102, screening out a target partition from the first-level partition.

After the primary partition is completed, the embodiment of the application can continuously judge whether the partition of each primary partition is reasonable or not, and whether the actual requirement is met or not. Specifically, a flowmeter, a flow pressure gauge, or the like may be installed in each primary partition to collect actual water usage data for each primary partition. Based on the obtained actual water data, the leakage condition of the first-level partition can be analyzed. The more serious the leakage, the more difficult and costly the management of the DMA partition. Therefore, in order to reduce the difficulty and cost of DMA partition, the management of the water supply network is finer and more flexible, and the leakage condition is reduced. The embodiment of the application screens the subareas with serious leakage conditions and continues to subareas. At this time S102 may be replaced with: and acquiring leakage data of each primary partition, and screening out a target partition according to the leakage data.

Here, the definition of the serious leakage is not limited, and for example, a leakage amount threshold or a leakage rate threshold may be set. When the corresponding leakage amount exceeds the threshold value or the leakage rate exceeds the threshold value, it is determined that the leakage is serious.

As another alternative embodiment of the present application, if the number of users and the total amount of users are not used for the preliminary partition in S101. In the embodiment of the present application, the target partition screening may also be performed by referring to the number of users and the total water consumption of the users at the same time. The primary partition is larger in scale (the number of users exceeds the upper limit of the number of users, the total water consumption of the users exceeds the upper limit of the water consumption of the users or the area of the corresponding area of the primary partition exceeds the upper limit of the area), or the partition with serious leakage is used as the target partition. At this time S102 may be replaced with: and acquiring at least one of leakage data, area, user distribution data and user water consumption data of the first-level partition, and screening a target partition from the first-level partition based on the acquired data.

S103, acquiring node characteristic data of each node in the target partition and pipe section characteristic data of pipe sections among the nodes, and dividing the target partition into a plurality of secondary partitions based on the node characteristic data and the pipe section characteristic data.

In order to achieve a reasonable secondary partitioning of the target partition. According to the method and the device, the relevance of each node in the target partition is analyzed, and the nodes with high relevance are partitioned to the same DMA partition as much as possible. Therefore, node management in the same DMA partition is more convenient and efficient, leakage analysis is facilitated, and engineering application cost is reduced. Since the dividing method for each target partition is the same, a single target partition will be described as an example. Referring to fig. 4, in S103, the processing operation on the single target partition includes: s1031 to S1032.

S1031, calculating the correlation (also called node correlation) between each node in the target partition according to the node characteristic data and the pipe section characteristic data.

In the embodiment of the present application, for two non-adjacent nodes, the correlation is set to 0. For two adjacent nodes, the embodiment of the application starts from the characteristics of the nodes and the characteristics of the connected pipe sections between the nodes to evaluate the correlation between the nodes. Wherein, the liquid crystal display device comprises a liquid crystal display device,

the node characteristic data includes the nodes: elevation, longitude, latitude, and water source.

The pipe segment characteristic data includes pipe segments: pipe inside diameter D, total flow Q1, night flow Q2, length L, pressure P, pipe section friction loss coefficient H.

The embodiment of the application does not limit the acquisition mode or the source of the node characteristic data and the pipe section characteristic data too much, and can be determined by a technician according to actual conditions. For example, in some embodiments, water usage data within a target zone may be acquired first to construct a corresponding water supply profile. And constructing a corresponding night water usage graph according to the night flow data in the water usage data. And simultaneously acquiring pressure distribution data of the target partition to form a water supply pressure distribution and a change chart. In S103, characteristic data and pipe section characteristic data are extracted from the water supply distribution map, the water supply pressure distribution map, the change map, and the night water use curve.

As an alternative embodiment of the present application, the calculation formula of the friction loss coefficient H of the pipe section is as follows:

wherein, each parameter is described as follows:

h: coefficient of friction loss of pipe section;

l: the length of the pipe section;

v: the water flow speed in the pipe section;

c: a Hazen-Williams coefficient, wherein the ABS, PVC, PE, PP, CPVC material pipe section c=150, new iron pipe c=130, concrete pipe c=120, old iron pipe c=100;

d: the pipe inner diameter of the pipe section.

After the node characteristic data and the pipe section characteristic data are acquired, the correlation degree S calculating method comprises the following steps:

1. Based on the pipe segment characteristics between two adjacent nodes, a correlation s1 (also referred to as a first correlation) between the nodes is calculated:

s1＝aD’+bQ1’+cQ2’+dL’+eP’+fH (2)

wherein, each parameter is described as follows:

d ', Q1', Q2', L ' and P ' are values after normalization of the pipe inner diameter D, the total flow Q1, the night flow Q2, the length L and the pressure P of the pipe section, respectively. The normalization method is not limited herein, and includes, but is not limited to, normalizing parameters of the actual single pipe segment by taking, for example, a maximum value of each parameter in the target partition as a denominator.

a. b, c, d, e, f are all preset weight coefficients. Wherein the values of a, d and f are all greater than the value of c, and the value of c is greater than the values of b and e. The weight coefficient values are described as follows:

for the pipe inside diameter, length and friction loss coefficient of pipe sections, the fixed attribute characteristics of the pipe sections can only be changed by changing the pipe sections, and the engineering cost corresponding to the change is extremely high. Therefore, the weight coefficients of the characteristic parameters are set to be larger, and pipe sections with high correlation of fixed attributes can be partitioned and managed in a relatively centralized manner. So as to reduce the management difficulty and the engineering application cost.

The correlation degree between the night flow Q2 and the pipe section leakage condition is higher, so that the weight coefficient is set to be relatively larger, the nodes with leakage can be relatively concentrated, and the pressure regulation and control are more convenient during leakage management. Thereby allowing the cost of leakage management to be reduced.

The total flow Q1 and pressure weight are set smaller to avoid too concentrated zoning of the high flow pipe segments. Meanwhile, the traffic has a reference index night traffic Q2, so that excessive influence of traffic dimension on node correlation can be avoided.

On the premise that the values of a, d and f are all larger than the value of c, and the value of c is larger than the values of b and e, the specific sizes of the weight coefficients are not excessively limited.

2. The degree of correlation s2 (also referred to as a second degree of correlation) between the nodes is calculated based on the characteristics of the nodes themselves.

Wherein K' is a normalized value of the spatial distance between the nodes. The spatial distance K between two nodes may be calculated from altitude, longitude, latitude, and normalized based on the maximum value of the spatial distance K within the target zone as the denominator. W is the water source correlation between nodes. In the embodiment of the application, the water source relation between the nodes is divided into three types of the same water source, independent water sources and related water sources. Wherein the same water source refers to the water source being identical between two nodes. Independent water sources means that the water sources between two nodes are completely different, and the water sources are mutually independent. Related water sources refer to the water sources between two nodes which are intersected or in an upstream-downstream water source relation. Wherein, the water source relativity is respectively: w=1 for the same water source, w=0 for the independent water source, and w=0.5 for the related water source. g and h are weight coefficients. Is set by the skilled person according to the requirements.

3. According to the situation of the neighboring nodes shared by the nodes, calculating a correlation s3 (also called a third correlation) between the nodes:

the neighbor node of a certain node refers to a node which is adjacent to the node and is provided with a pipe section for direct connection. The neighbor node shared by two nodes is the neighbor node of two nodes at the same time. The neighbor nodes of each node can be quickly determined through the topological graph of the water supply network. On the basis, the calculation formula of the correlation s3 between the node i and the node j is as follows:

wherein sn (i) and sn (j) are the number of neighbor nodes of the node i and the node j, respectively, and the number of neighbor nodes shared by the node i and the node j is set as a node u, and sn (u) is set as a node u.

4. And calculating the final node i and node j correlation S on the basis of the three different dimensional estimated correlations.

In the water supply network topological graph, the more neighbor nodes of a node are, the more closely related the neighbor nodes are. When DMA partitioning is performed, by partitioning closely related nodes into the same DMA partition, topology damage can be reduced. At the same time, the clustering can be made to approach more dense division, thereby reducing the number of boundary pipe segments. And further, the installation cost and the management cost of the DMA partition are reduced, and the engineering application cost is reduced. Therefore, the final similarity S can be calculated using the following formula.

Where n is the total number of nodes in the target partition, and max (sn) is the maximum number of neighbor nodes among the number of neighbor nodes of each node in the target partition. sn (i) and sn (j) are the number of neighbor nodes of node i and node j, respectively.

In view of practical engineering applications, management and maintenance of pipe sections (such as analysis of pipe section leakage and repair) is a very costly item. Therefore, in the embodiment of the present application, the formula (5) sets the maximum weight coefficient when calculating the final degree of correlation S between the node i and the node j, taking the degree of correlation S1 as a serious consideration. So that the finally obtained correlation S can better show the correlation of the nodes and the pipe sections among the nodes. Based on the above, the embodiment of the application divides the secondary partition, so that the node cluster is more close to the dense partition of the nodes and the pipe sections, and the number of the boundary pipe sections is reduced. And further, the installation cost and the management cost of the DMA partition are reduced, and the engineering application cost is reduced.

As an alternative embodiment of the present application, only the correlation s1, the correlation s2, or the correlation s3 may be selected as the correlation between nodes. At this time, S103 may be modified to obtain node feature data of each node in the target partition, and/or pipe segment feature data of pipe segments between nodes, and divide the target partition into a plurality of secondary partitions based on the node feature data and/or the pipe segment feature data. S1031 may be modified as: and calculating the correlation degree among all nodes in the target partition according to the node characteristic data and/or the pipe section characteristic data. The method is characterized in that the correlation between two nodes is comprehensively evaluated from three dimensions of pipe section conditions among the nodes, node self conditions and common neighbor node conditions among the nodes. Comprehensive and comprehensive evaluation of node relevance can be realized. The obtained correlation data is more accurate and reliable.

S1032, based on the correlation degree among the nodes in the target partition, the nodes in the target partition are clustered, and the target partition is divided into a plurality of secondary partitions according to the clustering result.

Assuming that there are n nodes in the target partition, after the operation of S1031, correlation data between each node and other n-1 nodes can be obtained. Based on the correlation data, the nodes can be clustered to realize the division of the nodes. The embodiment of the application does not limit the specific clustering method too much. Including but not limited to, for example: k-means algorithm, K-center algorithm, CLARANS algorithm, EM algorithm, OPTICS algorithm, DBSCAN algorithm, etc. For example, in some embodiments, the relevance of a node to itself may be set to a fixed constant, such as 0. The correlation data of each node at this time is a 1×n-dimensional data. And then clustering the n nodes based on clustering algorithms such as a K-means algorithm and the like.

As an alternative embodiment of the present application, to improve the reliability and practicality of the clustering result. Some clustering constraints may be set. For example, a range of the number of packet nodes per type, etc. may be set.

After the clustering result of the nodes in the target partition is obtained, the nodes contained in the single type are divided into the same two-level partition, and then the target partition can be divided.

By way of example, assume that primary partition 1 and primary partition 3 are determined to be target partitions on the basis of FIG. 3. The processing may be performed using the operations of S1031 and S1032, at which time reference may be made to fig. 5. For primary partition 3, the clustering results classify node 13, node 20, node 22, and node 23 as one class, and node 17, node 24, node 29, node 30, node 33, node 38, and node 39 as another class. The two nodes can be clustered at this time to partition the secondary partition 3 and the secondary partition 4. Similarly, the primary partition 1 may be divided into the secondary partition 1 and the secondary partition 2.

As an optional embodiment of the application, in order to improve the effectiveness of the clustering result, the result of the secondary partition is more in line with the requirement of actual DMA partition management, and the engineering application cost is reduced. Referring to fig. 6, S1032 may be replaced with: s10321 and S10322.

S10321, based on the correlation degree among the nodes in the target partition, carrying out multiple clustering treatment on the nodes in the target partition to obtain multiple clustering results, and determining the secondary partition result of the target partition under each clustering result.

In the embodiment of the present application, a plurality of different clustering algorithms may be simultaneously used to cluster the nodes in the target partition, or a single clustering algorithm may be used to cluster the nodes in the target partition multiple times, which is not limited herein.

After a plurality of clustering results are obtained, the secondary partition division corresponding to the clustering results can be realized according to the node condition contained in each type in the clustering results. At this time, each clustering result has a secondary partition result for the target partition.

S10322, comparing the multiple secondary partition results, and screening out one secondary partition result with the minimum number of boundary pipe sections.

In the embodiment of the application, only one result with the minimum boundary number is reserved in the multiple secondary partition results by comparing the number of the boundary pipe sections. The number of the boundary pipe sections of the DMA partition finally obtained can be reduced as much as possible, so that the engineering application cost is reduced.

S104, taking the second-level partition and the first-level partition which are not divided as independent metering partitions of the water supply network.

After the division of the secondary partition is completed, the embodiment of the application completes the DMA partition operation of the water supply network. At this time, all the primary partitions which are not subdivided and the secondary partitions obtained after the target partitions are divided can be used as DMA partitions in the embodiment of the present application.

Illustrated by way of example. Based on the example shown in fig. 5, the primary partition 2, the secondary partition 1, the secondary partition 2, the secondary partition 3, and the secondary partition 4 are DMA partitions in this example. At this time, the DMA partition result of the water supply network may be referred to in fig. 7, so as to obtain the corresponding DMA partition 4, DMA partition 1, DMA partition 2, DMA partition 5, and DMA partition 3.

After S104, the resulting DMA partition may be put into actual engineering use.

S105, monitoring the independent metering partition, and determining the partition to be updated, wherein the partition to be updated is required to be updated.

In consideration of actual engineering application, the demand of urban water is also constantly changing, so that the fixed DMA partition is difficult to adapt to the actual demand for a long time. Based on this, after completing the DMA partitioning of the water supply network in S101 to S104, the embodiment of the present application further continues to monitor how the actual situation of each DMA partition is, and determines whether to need to perform adjustment and update. The frequency of monitoring, timing, etc. may be set by a skilled person, and is not limited thereto. Since the method for determining whether adjustment is required for each DMA partition is the same in detail, referring to fig. 8, a single DMA is taken as an example as follows:

S1051, obtaining at least one index data of the number of users, the water quality condition, the leakage condition, the user complaint condition and the water use difference degree between the independent metering partition and other independent metering partitions.

S1052, judging whether the independent metering partition is abnormal or not according to the acquired index data, and judging that the independent metering partition is a partition to be updated which needs to be partitioned if the independent metering partition is abnormal.

When the number of users in a single DMA partition is excessive, the management difficulty and cost of the DMA partition is significant. The water quality condition and the user complaint condition are directly related to the actual water consumption condition of the users in the DMA partition, and when the water quality condition is poor or the user complaint condition is more, the DMA partition has a certain problem. The leakage condition can be indexes such as leakage quantity or leakage rate, and when the leakage condition is serious, the DMA partition has a certain problem, which is not beneficial to leakage management. Therefore, any one or more of these index data can be used to determine whether the DMA partition matches the actual water demand or needs to be adjusted. Specifically, corresponding thresholds may be set for the number of users, the water quality condition, the user complaint condition, and the leakage condition, respectively. When any index data exceeds the corresponding threshold value, the DMA partition can be judged to be abnormal.

When the water difference between a certain DMA partition and other DMA partitions is too large, the DMA partition is unreasonable to divide. For example, when the DMA partition uses much more water than other DMA partitions, this indicates that the water pressure within the DMA partition is very high or that the leak condition is very severe. Therefore, the embodiment of the application can also calculate the water difference degree between the DMA partition and other DMA partitions, so as to judge whether the partition needs to be updated. The specific water difference calculating method is not limited herein, and may be set by a skilled person. For example, in some embodiments, the difference in water usage for the DMA partition from the average or mode of water usage for all DMA partitions may be calculated. And when the difference value is larger than a preset difference value threshold value, evaluating that the water consumption difference degree is overlarge.

In practical application, a technician can select any data of the number of users, the water quality condition, the leakage condition, the user complaint condition and the water use difference degree as a judgment basis according to the requirements. And are not limited herein.

If the monitoring result in S105 is that there is no DMA partition that needs to be updated, the DMA partition of the water supply network does not need to be updated, and at this time, the latest DMA partition can be maintained.

And S106, if the partition to be updated is a primary partition, taking the partition to be updated as a target partition, returning to execute the operation of S103, and dividing the partition to be updated into a plurality of independent metering partitions.

And S107, if the partition to be updated is a secondary partition, returning to execute the operation of S103 based on the target partition to which the partition to be updated belongs, and re-dividing the target partition to which the partition to be updated belongs into a plurality of independent metering partitions.

Partition updates of embodiments of the present application include two cases:

1. the partition to be updated is a primary partition which is not divided.

2. The partition to be updated is a secondary partition obtained via partitioning the target partition.

When the partition to be updated is a primary partition which is not divided, the primary partition is not suitable as a single DMA partition. Therefore, the embodiment of the application subdivides the primary partition to obtain a plurality of DMA partitions which more meet the actual engineering requirements. When the partition to be updated is a secondary partition, it is indicated that the secondary partition is not suitable as a DMA partition. However, the boundary adjustment is performed on the two-stage partition alone, which may cause a chain reaction of the adjacent DMA partition, so that the adjacent DMA partition may have a problem. Therefore, the embodiment of the application will take the target partition described by the secondary partition as the object again, and perform DMA partition operation based on the latest node related feature data. So that the retrieved DMA partition may be more suited to the actual water and management requirements. Meanwhile, since the update of the DMA partition in the embodiment of the application is based on the original DAM partition frame. And therefore fewer boundaries of updates are required relative to each update. In practical application, the workload of engineering change is relatively less, so that on the basis of meeting the practical requirements, the embodiment of the application can save a great amount of engineering application cost.

Corresponding to the method for independent metering and partitioning of a water supply network described in the above embodiments, fig. 9 shows a schematic structural diagram of the device for independent metering and partitioning of a water supply network provided in the embodiment of the present application, and for convenience of explanation, only the portions relevant to the embodiment of the present application are shown.

Referring to fig. 9, the independent metering and partitioning device of the water supply network includes:

the primary partition module 91 is configured to obtain natural boundary data of a region to be partitioned, and partition a water supply network of the region to be partitioned into a plurality of primary partitions based on the natural boundary data.

The partition screening module 92 is configured to obtain leakage data of each primary partition, and screen a target partition from the primary partitions according to the leakage data.

A fine partition module 93, configured to calculate a node correlation between each node in the target partition based on the node characteristic data of each node in the target partition and the pipe section characteristic data of each pipe section; and carrying out clustering processing on the nodes in the target partition according to the node relevance, and dividing the target partition into a plurality of secondary partitions according to a clustering result.

The partition determining module 94 is configured to use the second-level partition and the first-level partition that are not divided as independent metering partitions of the water supply network.

The partition monitoring module 95 is configured to monitor the independent metering partition, and determine a partition to be updated in which a partition update is required.

The partition updating module 96 is configured to, when the partition to be updated is a secondary partition, return to perform an operation of dividing the target partition into a plurality of secondary partitions based on node characteristic data of each node and/or pipe segment characteristic data of each pipe segment in the target partition based on the target partition to which the partition to be updated belongs.

As an embodiment of the present application, the subdivision module 93 includes:

the first calculation module is used for calculating a first correlation degree between each adjacent node in the target partition according to the pipe section characteristic data;

the second calculation module is used for calculating a second correlation degree between each two adjacent nodes in the target partition according to the node characteristic data;

the third calculation module is used for calculating a third relativity between each adjacent node in the target partition according to the adjacent condition of each node in the target partition;

calculating the node correlation between each adjacent node in the target partition based on the following formula:

s is the node correlation degree of the node i and the node j, S1, S2 and S3 are the first correlation degree, the second correlation degree and the third correlation degree of the node i and the node j respectively, n is the total number of nodes in the target partition, max (sn) is the maximum value of the number of neighbor nodes of each node in the target partition, sn (i) and sn (j) are the number of neighbor nodes of the node i and the node j respectively, and the node i and the node j are any two adjacent nodes in the target partition.

The clustering module is used for carrying out multiple clustering treatment on the nodes in the target partition according to the node correlation degree to obtain multiple clustering results, and determining partition division results of the target partition corresponding to each clustering result; each partition division result comprises a plurality of secondary partitions;

and the result screening module is used for comparing the partition dividing results and screening out one partition dividing result with the least number of boundary pipe sections.

As one embodiment of the present application, a first computing module includes:

the pipe section feature data includes: pipe inner diameter D, total flow Q1, night flow Q2, length L, pressure P and pipe friction loss coefficient H of the pipe section;

calculating the first correlation between each adjacent node in the target partition based on the following formula;

s1＝aD’+bQ1’+cQ2’+dL’+eP’+fH

wherein s1 is the first correlation degree of the node i and the node j, D ', Q1', Q2', L ' and P ' are values after normalization processing of the pipe inner diameter D, the total flow Q1, the night flow Q2, the length L and the pressure P of the pipe section connecting the node i and the node j, H is a pipe section friction loss coefficient of the pipe section connecting the node i and the node j, a, b, c, D, e, f is a preset weight coefficient, wherein the values of a, D and f are larger than the value of c, and the value of c is larger than the values of b and e.

As an embodiment of the present application, the third computing module includes:

calculating the third correlation between each adjacent node within the target partition according to the following formula:

and s3 is the third correlation degree of the node i and the node j, the neighbor node shared by the node i and the node j is set as a node u, and sn (u) is set as the number of the node u.

As one embodiment of the present application, the second computing module includes:

the node characteristic data includes: elevation, longitude, latitude, and water source of the node;

and calculating a second correlation degree between each adjacent node in the target partition according to the node characteristic data, wherein the second correlation degree comprises the following steps:

calculating a space distance K between each adjacent node in the target zone according to the altitude, the longitude and the latitude;

determining the water source correlation between each adjacent node in the target partition according to the water source;

calculating the second degree of correlation between each adjacent node within the target partition based on the formula:

wherein s2 is the second correlation degree of the node i and the node j, K' is a normalized value of the spatial distance K between the node i and the node j, W is the water source correlation degree between the node i and the node j, and g and h are preset weight coefficients.

As one embodiment of the present application, the coefficient of friction loss of the pipe segment is determined according to the following formula:

wherein H, L, V, C and D are the pipe section friction loss coefficient, the length, the pipe section water flow velocity, the Hazen-Williams coefficient and the pipe inner diameter, respectively.

The process of implementing respective functions by each module in the independent metering partition device of the water supply network provided in this embodiment of the present application may refer to the foregoing description of the embodiment shown in fig. 1 and other related method embodiments, which are not repeated herein.

It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".

In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance. It will also be understood that, although the terms "first," "second," etc. may be used in this document to describe various elements in some embodiments of the present application, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first table may be named a second table, and similarly, a second table may be named a first table without departing from the scope of the various described embodiments. The first table and the second table are both tables, but they are not the same table.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

The method for independently metering and partitioning the water supply network provided by the embodiment of the application can be applied to terminal equipment such as mobile phones, tablet computers, wearable equipment, vehicle-mounted equipment, augmented reality (augmented reality, AR)/Virtual Reality (VR) equipment, notebook computers, ultra-mobile personal computer (UMPC), netbooks, personal digital assistants (personal digital assistant, PDA) and the like, and the specific types of the terminal equipment are not limited.

For example, the terminal device may be a cellular telephone, a cordless telephone, a Session initiation protocol (Session InitiationProtocol, SIP) telephone, a wireless local loop (Wireless Local Loop, WLL) station, a personal digital assistant (Personal Digital Assistant, PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a car networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite radio, a wireless modem card, a television Set Top Box (STB), a customer premise equipment (customer premise equipment, CPE) and/or other devices for communicating over a wireless system, as well as next generation communication systems, such as a terminal device in a 5G network or a terminal device in a future evolved public land mobile network (Public Land Mobile Network, PLMN) network, etc.

Fig. 10 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 10, the terminal device 10 of this embodiment includes: at least one processor 100 (only one shown in fig. 10), a memory 101, said memory 101 having stored therein a computer program 102 executable on said processor 100. The processor 100, when executing the computer program 102, implements the steps of the above-described embodiment of the independent metering and partitioning method for each water supply network, such as steps 101 to 107 shown in fig. 1. Alternatively, the processor 100 may perform the functions of the modules/units of the apparatus embodiments described above, such as the functions of the modules 91 to 96 of fig. 9, when executing the computer program 102.

The terminal device 10 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 100, a memory 101. It will be appreciated by those skilled in the art that fig. 10 is merely an example of the terminal device 10 and is not limiting of the terminal device 10, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the terminal device may also include an input transmitting device, a network access device, a bus, etc.

The processor 100 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 101 may in some embodiments be an internal storage unit of the terminal device 10, such as a hard disk or a memory of the terminal device 10. The memory 101 may also be an external storage device of the terminal device 10, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 10. Further, the memory 101 may also include both an internal storage unit and an external storage device of the terminal device 10. The memory 101 is used for storing an operating system, application programs, boot loader (BootLoader), data, other programs, etc., such as program codes of the computer program. The memory 101 may also be used for temporarily storing data that has been transmitted or is to be transmitted.

In addition, it will be clearly understood by those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The embodiment of the application also provides a terminal device, which comprises at least one memory, at least one processor and a computer program stored in the at least one memory and capable of running on the at least one processor, wherein the processor executes the computer program to enable the terminal device to realize the steps in any of the method embodiments.

Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements steps that may implement the various method embodiments described above.

The embodiments of the present application provide a computer program product which, when run on a terminal device, causes the terminal device to perform the steps of the method embodiments described above.

The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each method embodiment described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. An independent metering and partitioning method for a water supply network, comprising the steps of:

natural boundary data, administrative region division data, user distribution data and user water consumption data of a region to be divided are obtained, and a water supply network of the region to be divided is divided into a plurality of primary partitions based on the natural boundary data, the administrative region division data, the user distribution data and the user water consumption data;

obtaining leakage data of each primary partition, and screening a target partition from the primary partitions according to the leakage data, wherein the target partition is a primary partition with serious leakage;

according to the node correlation degree, carrying out clustering processing on the nodes in the target partition, and dividing the target partition into a plurality of secondary partitions according to a clustering result;

the secondary partition and the primary partition which is not divided are used as independent metering partitions of the water supply network, wherein the primary partition which is not divided is a primary partition except the target partition;

if the partition to be updated is the secondary partition, based on the target partition to which the partition to be updated belongs, returning to execute the operation of dividing the target partition into a plurality of secondary partitions based on node characteristic data of each node and/or pipe section characteristic data of each pipe section in the target partition;

the calculating the node correlation between the nodes in the target partition based on the node characteristic data of the nodes in the target partition and the pipe section characteristic data of the pipe sections comprises the following steps:

calculating a first correlation between adjacent nodes in the target partition according to the pipe section characteristic data;

calculating a second correlation degree between each adjacent node in the target partition according to the node characteristic data;

calculating a third correlation degree between each adjacent node in the target partition according to the adjacent condition of each node in the target partition;

wherein S is the node correlation degree of the node i and the node j, S1, S2 and S3 are the first correlation degree, the second correlation degree and the third correlation degree of the node i and the node j respectively, n is the total number of nodes in the target partition, max (sn) is the maximum value of the number of neighbor nodes of each node in the target partition, sn (i) and sn (j) are the number of neighbor nodes of the node i and the node j respectively, and the node i and the node j are any two adjacent nodes in the target partition;

And calculating a third correlation degree between each adjacent node in the target partition according to the adjacent condition of each node in the target partition, including:

and s3 is the third correlation degree of the node i and the node j, the neighbor node shared by the node i and the node j is set as a node u, sn (u) is the number of the node u, wherein the neighbor node of the node i refers to a node which is adjacent to the node i and is directly connected with a pipeline.

2. The method for independent metering and partitioning a water supply network according to claim 1, wherein the clustering processing is performed on the nodes in the target partition according to the node correlation, and the target partition is partitioned into a plurality of secondary partitions according to a clustering result, comprising:

carrying out multiple clustering treatment on the nodes in the target partition according to the node correlation degree to obtain multiple clustering results, and determining partition dividing results of the target partition corresponding to each clustering result; each partition division result comprises a plurality of secondary partitions;

comparing the partition dividing results, and screening out one partition dividing result with the least number of boundary pipe sections.

3. The method for individually metering and partitioning a water supply network according to any one of claims 1 to 2, wherein after monitoring the individually metering and partitioning, determining the partition to be updated in which the partition update is required, further comprises:

and if the partition to be updated is the primary partition which is not divided, taking the partition to be updated as a target partition, and returning to execute the operation of dividing the target partition into a plurality of secondary partitions based on the node characteristic data of each node and/or the pipe section characteristic data of each pipe section in the target partition.

4. The method of independent metering and zoning a water supply network according to claim 1, wherein the pipe segment characteristic data comprises: pipe inner diameter D, total flow Q1, night flow Q2, length L, pressure P and pipe friction loss coefficient H of the pipe section;

and calculating a first correlation between each adjacent node in the target partition according to the pipe section characteristic data, wherein the first correlation comprises the following steps:

s1＝aD’+bQ1’+cQ2’+dL’+eP’+fH

5. The method of independent metering and partitioning a water supply network according to claim 1, wherein the node characteristic data comprises: elevation, longitude, latitude, and water source of the node;

6. The method of independent metering and zoning a water supply network according to claim 4, wherein the coefficient of friction loss of the pipe section is determined according to the following formula:

7. A terminal device, characterized in that it comprises a memory, a processor, on which a computer program is stored which is executable on the processor, when executing the computer program, realizing the steps of the method according to any of claims 1-6.

8. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 6.