Water service pipe network management system based on GIS

Abstract

The invention relates to the technical field of water affair management, in particular to a water affair pipe network management system based on a GIS (Geographic Information System), which comprises a GIS map module which is used for dynamically displaying real-time states of monitoring points on a GIS map and visualizing a connection relationship between pipelines and nodes through topological analysis of the GIS; according to the application, a GIS map is taken as a core carrier, strong association of space coordinates-asset attributes-real-time states is constructed, and quantitative analysis and intelligent decision-making capabilities are endowed to the system through closed-loop linkage of four algorithms of water leakage detection, hydraulic simulation, path optimization and pipe network extension.

Description

Technical Field

[0001] This invention relates to the field of water management technology, specifically to a GIS-based water network management system. Background Technology

[0002] Traditional water pipe network management systems often adopt a separate management model of "tables + drawings". The distribution of pipe network relies on paper drawings or static CAD files. The two are not linked in real time and cannot be intuitively displayed through GIS to show the spatial topology of pipes, valves and nodes, such as which areas will be affected by the closure of a certain valve. This leads to valve closure decisions relying on experience, which can easily cause misoperation. At the same time, real-time data such as pressure and flow cannot be dynamically displayed on the map, making it difficult to quickly locate abnormal areas. Summary of the Invention

[0003] In view of the above problems, the present invention proposes a GIS-based water supply network management system, comprising:

[0004] The GIS map module includes displaying the real-time status of monitoring points on a GIS map using dynamic icons, and visualizing the connection relationships of pipelines and nodes through GIS topology analysis.

[0005] The data management module acquires real-time monitoring dynamic data and performs preprocessing and benchmark calibration on the acquired monitoring dynamic data.

[0006] The analysis and decision-making module includes a leakage monitoring submodule, a hydraulic condition simulation submodule, a maintenance path optimization submodule, and a pipeline expansion optimization submodule;

[0007] The leakage monitoring submodule is based on the pressure-flow coupling analysis method to locate potential leaks in the pipeline network.

[0008] The hydraulic condition simulation submodule simulates the pressure and flow distribution of the pipeline network under different operating conditions based on the node-pipe segment model, assisting in the evaluation of the pipeline network's carrying capacity. When a leak point is predicted, it is treated as an abnormal node, substituted into the node flow balance equation, and the pressure / flow distribution of the entire pipeline network is recalculated.

[0009] The maintenance route optimization submodule includes planning the shortest inspection route for maintenance personnel based on the improved Dijkstra algorithm, GIS coordinates of maintenance points, priority weights of maintenance points, and traffic restriction information in the GIS road layer.

[0010] The pipeline expansion optimization submodule calculates the optimal pipeline expansion scheme based on a cost-benefit model; it determines the expansion scheme based on historical leakage data and maintenance costs, and updates the expanded pipeline topology data to the GIS data.

[0011] The system management module includes setting corresponding operation permissions for different operators and setting up a data maintenance database.

[0012] Preferably, the method of locating potential pipeline leaks based on pressure-flow coupling analysis includes: establishing a probability index P(x,y);

[0013]

[0014] Where (x,y) are the GIS coordinates of the area to be detected, and ΔP(x,y) represents the difference between the actual flow rate and the normal flow rate at the detection point. This represents the regional average normal pressure. Let ΔQ(x,y) represent the average normal flow rate for the region, and let ΔQ(x,y) represent the difference between the actual pressure and the normal pressure at the detection point. , The weighting coefficient is dynamically adjusted based on the pipeline material.

[0015] A water leakage alarm is triggered when P(x,y)>0.8, and the candidate area of ​​the landing point is output in combination with GIS coordinates.

[0016] Preferably, the pressure and flow distribution of the pipeline network under different operating conditions is simulated based on the node-segment model to assist in the evaluation of the pipeline network's carrying capacity, including: calculating the head loss of the pipe segment using the Hardy-Cross method. ,

[0017] Where Q is the flow rate of the pipe section, n is the flow index (n=2 for turbulent flow), and k is the resistance coefficient;

[0018] A flow balance equation is constructed based on the premise that the sum of the inflows to any node equals the sum of the outflows.

[0019] ,in, The flow rate in the pipe segment flowing into node i is positive (inflow to node i) and negative (outflow to node i), where q is the user's water consumption and m is the number of nodes. The flow rate in the pipe segment is corrected through an iterative algorithm until the node flow balance error is < 0.01 m³ / s, at which point the result converges. The input is based on the leak location results, treating the leak as an abnormal node and substituting it into the node flow balance equation to recalculate the pressure / flow distribution of the entire pipe network. The output results are the flow rate, velocity, and head loss of each pipe segment. The pressure and free head of each node can be directly linked to a GIS map for visualization.

[0020] Preferably, based on the improved Dijkstra algorithm, planning the shortest inspection route for maintenance personnel includes: calculating the comprehensive cost of the route C(i,j);

[0021] C(i,j)=γd(i,j)+(1-γ)t(i,j)w:

[0022] Where d(i,j) is the straight-line distance from node i to j calculated based on GIS coordinates, t(i,j) is the travel time between the road segments, w is the priority weight of the maintenance point, and γ is the distance weight coefficient. The node with the lowest cost is selected to plan the path. When γ=0.6, the distance is shortened first, and the starting point is the GIS coordinates of the maintenance center. The constraint is to avoid the construction section. The output is the optimal path order.

[0023] Preferably, the optimal pipeline expansion scheme is calculated based on a cost-benefit model, including:

[0024] Calculate the objective function to maximize net benefit NB: NB = ,in, For the water supply benefits in year t, Let r be the cost in year t, r be the discount rate, and T be the design life of the pipeline network.

[0025] Compared with existing technologies, this technical solution has the following advantages: This application uses GIS maps as the core carrier to construct a strong correlation between spatial coordinates, asset attributes, and real-time status. Through the closed-loop linkage of four major algorithms—leakage detection, hydraulic simulation, path optimization, and pipeline expansion—the system is endowed with quantitative analysis and intelligent decision-making capabilities. This application, through "spatialization, intelligence, collaboration, and closed-loop," can significantly reduce pipeline leakage rates, reduce operation and maintenance costs, and improve emergency response speed, providing core support for the refined and intelligent management of urban water pipeline networks. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 The diagram shown is a schematic of the system modules. Detailed Implementation

[0028] To enable those skilled in the art to better understand the technical solutions of this application, the present invention will be further described in detail below with reference to the accompanying drawings and preferred embodiments.

[0029] like Figure 1As shown, a GIS-based water pipeline network management system includes a GIS map module. This module displays the real-time status of monitoring points on a GIS map using dynamic icons, providing a visual representation of the pipeline network distribution and monitoring data through GIS. Furthermore, it visualizes the connections between pipelines and nodes through GIS topology analysis. The GIS map module interface layout includes a top toolbar, a layer control area, a central map canvas, and a real-time monitoring panel. The top toolbar includes basic operations: zoom (e.g., ± buttons / mouse wheel); pan (e.g., drag); full map display; and layer reset.

[0030] Advanced tools include: distance measurement for calculating pipe segment length; area measurement for measuring area coverage; spatial query for selecting pipe network assets within a region; and map printing / export.

[0031] The layer control area includes a list of layers: such as the pipe layer, which is divided into sub-layers by material / diameter, such as DN300 ductile iron pipe; the node layer, including valves / water meters / pump stations; the monitoring point layer, including pressure sensors / flow meters; and the auxiliary layer, including roads / buildings / water systems, used for spatial positioning.

[0032] Interactive features include layer selection, transparency adjustment, legend explanations, and color coding, such as red pipes indicating abnormal pressure and green pipes indicating normal pressure.

[0033] The intermediate map canvas includes: a base map, which includes high-resolution satellite maps / vector maps, and supports switching;

[0034] Pipeline network element rendering: This includes displaying pipes as lines with line widths corresponding to diameters, and nodes as icons, such as gate valve icons for valves.

[0035] Dynamic annotation: Feature attributes are displayed when the mouse hovers over the element.

[0036] Real-time monitoring panel: includes data cards: displaying real-time pressure (MPa), flow rate (m³ / h), water turbidity / residual chlorine at key monitoring points; data exceeding the standard are highlighted in red and flash.

[0037] Alarm list: sorted by urgency, such as leak alarm: P0012 pipe section, pressure drop of 0.15MPa. Clicking on the alarm item will automatically locate the corresponding position on the map.

[0038] The data management module acquires real-time monitoring dynamic data, which includes data such as GIS coordinates of monitoring points, pressure values, flow values, and collection timestamps obtained through pressure sensors and electromagnetic flow meters deployed in the pipeline network. The module preprocesses and calibrates the acquired monitoring dynamic data against corresponding monitoring points in the GIS map, filters monitoring data such as flow and pressure by time / region, and generates trend charts.

[0039] The analysis and decision-making module includes a leakage monitoring submodule, a hydraulic condition simulation submodule, a maintenance path optimization submodule, and a pipeline expansion optimization submodule;

[0040] The leakage monitoring submodule is based on the pressure-flow coupling analysis method to locate potential leaks in the pipeline network.

[0041] The leak monitoring submodule upgrades the traditional leak detection mode that relies on manual inspection to an intelligent mode of "automatic early warning + precise positioning" through "real-time data, model-based analysis, spatialized results, and coordinated handling". This reduces the leak detection time from "days" to "hours" and improves the leak location accuracy from "kilometers" to "hundreds of meters", significantly reducing the leak rate and maintenance costs.

[0042] The hydraulic condition simulation submodule simulates the pressure and flow distribution of the pipeline network under different operating conditions, such as peak water usage and valve closure during maintenance, based on a node-pipe segment model, to assist in evaluating the network's carrying capacity. Essentially, it constructs the pipeline network topology and hydraulic equations to quantitatively calculate parameters such as pressure and flow under different scenarios. When a leak is predicted, the leak point is treated as an abnormal node, substituted into the node flow balance equation, and the pressure / flow distribution of the entire pipeline network is recalculated.

[0043] The maintenance route optimization submodule includes a method based on the improved Dijkstra algorithm to plan the shortest inspection route for maintenance personnel, taking into account the location of maintenance points, road restrictions, pipeline priorities, GIS coordinates of maintenance points, priority weights of maintenance points, and traffic restriction information in the GIS road layer.

[0044] The pipeline expansion and optimization submodule is based on a cost-benefit model. When water demand increases, it calculates the optimal pipeline expansion plan to balance construction costs and water supply capacity. It determines the expansion plan based on historical leakage data and maintenance costs, and updates the expanded pipeline topology data to the GIS data.

[0045] The system management module includes setting corresponding operation permissions for different operators. For example, when the operator is an administrator, their permissions are configured to have full permissions; when the operator is a dispatcher, their permissions are configured to rely on operation detection; and when the operator is a maintenance personnel, their permissions are configured to only view path / asset information. It also includes setting up a data maintenance database, which automatically backs up data every morning and supports one-click recovery. In addition, it also supports log auditing to record user operations.

[0046] The method for locating potential leaks in the pipeline network based on pressure-flow coupling analysis includes: establishing a probability index P(x,y);

[0047]

[0048] Where (x,y) are the GIS coordinates of the area to be detected, and ΔP(x,y) represents the difference between the actual flow rate and the normal flow rate at the detection point. This represents the regional average normal pressure. Let ΔQ(x,y) represent the average normal flow rate for the region, and let ΔQ(x,y) represent the difference between the actual pressure and the normal pressure at the detection point. , The weighting coefficient is dynamically adjusted based on the pipeline material.

[0049] A water leakage alarm is triggered when P(x,y)>0.8, and the candidate area of ​​the landing point is output in combination with GIS coordinates.

[0050] This model, based on a node-segment model, simulates the pressure and flow distribution of a pipeline network under different operating conditions, such as peak water usage and valve closures during maintenance. It assists in assessing the network's carrying capacity. Essentially, this involves constructing the network topology and hydraulic equations to quantify parameters such as pressure and flow under different scenarios. Nodes include water distribution points, water meters, valves, and pumping stations, requiring input parameters such as spatial coordinates (GIS positioning) and ground elevation for calculating free head. Segments include length, diameter, and material. The topological relationship is established through connections between nodes and segments, such as segment P1 connecting nodes J1-J2, constructing a logical network for water flow direction. This includes calculating segment head loss using the Hardy-Cross method. , Where Q is the flow rate of the pipe section, n is the flow index (n=2 for turbulent flow), and k is the resistance coefficient;

[0051] A flow balance equation is constructed based on the premise that the sum of the inflows to any node equals the sum of the outflows.

[0052] ,in, The flow rate in the pipe segment flowing into node i is positive (inflow to node i) and negative (outflow to node i), where q is the user's water consumption and m is the number of nodes. The flow rate in the pipe segment is corrected using an iterative algorithm until the node flow balance error is < 0.01 m³ / s, at which point the result converges. The iterative solution involves iteratively correcting the flow rate in the pipe network to satisfy energy conservation, including step 1: calculating the head loss of each pipe, i.e., calculating the head loss of the pipe segment based on the current flow rate Q and using the Hardy-Cross method. Step 2: Calculate the total head loss ,like If the flow rate is less than the accuracy threshold, convergence occurs; if it is in a non-convergent state, a flow correction value is calculated to adjust the pipeline flow rate until convergence is achieved. When a leak is predicted, the leak point is treated as an abnormal node and substituted into the node flow balance equation to recalculate the pressure / flow distribution of the entire pipe network; the output results are the flow rate, velocity, and head loss of each pipe segment; the pressure and free head of each node can be directly linked to a GIS map for visualization. The output results can indicate the impact range of the leak on the surrounding pipe network, such as which areas experience sudden pressure drops and insufficient flow; and simulate the optimal valve closure scheme during valve maintenance, such as whether valve closure will lead to a large-scale water outage.

[0053] Based on the improved Dijkstra algorithm, the shortest inspection route for maintenance personnel is planned, including calculating the comprehensive cost of the route C(i,j).

[0054] C(i,j)=γd(i,j)+(1-γ)t(i,j)w:

[0055] Where d(i,j) is the straight-line distance from node i to j calculated based on GIS coordinates, t(i,j) is the travel time between the road segments, w is the priority weight of the maintenance point, and γ is the distance weight coefficient. The node with the lowest cost is selected to plan the path. When γ=0.6, the distance is shortened first, and the starting point is the GIS coordinates of the maintenance center. The constraint is to avoid the construction section. The output is the optimal path order.

[0056] Based on the cost-benefit model, the optimal pipeline expansion scheme is calculated as follows:

[0057] Calculate the objective function to maximize net benefit NB: NB = ,in, For the water supply benefits in year t, Let r be the cost in year t, r be the discount rate, and T be the design life of the pipeline network. The logical examples used in this application include:

[0058] Users can discover abnormal pressure in a certain area in the GIS map module → click "Leak Detection" → jump to the leak detection submodule, and automatically select the abnormal area;

[0059] After the leak is detected, click "Simulate Impact" → the hydraulic condition simulation submodule will automatically load the leak parameters and generate a valve shut-off scheme;

[0060] After determining the maintenance point, click "Plan Path" → Maintenance Path Optimization submodule to import the maintenance point coordinates and generate the optimal inspection route;

[0061] If the same pipe section is repaired multiple times, the system will automatically prompt "This pipe section is severely aged" → It is recommended to enter the pipeline expansion and optimization submodule to evaluate the replacement plan.

[0062] The above description is only one preferred embodiment of the present invention. Ordinary changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention should be included within the protection scope of the present invention.

Claims

1. A GIS-based water supply network management system, characterized in that, include: The GIS map module includes displaying the real-time status of monitoring points on a GIS map using dynamic icons, and visualizing the connection relationships of pipelines and nodes through GIS topology analysis. The data management module acquires real-time monitoring dynamic data and performs preprocessing and benchmark calibration on the acquired monitoring dynamic data. The analysis and decision-making module includes a leakage monitoring submodule, a hydraulic condition simulation submodule, a maintenance path optimization submodule, and a pipeline expansion optimization submodule; The leakage monitoring submodule is based on the pressure-flow coupling analysis method to locate potential leaks in the pipeline network. The hydraulic condition simulation submodule simulates the pressure and flow distribution of the pipeline network under different operating conditions based on the node-pipe segment model, and assists in evaluating the pipeline network's carrying capacity. When a leak point is predicted, the leak point is regarded as an abnormal node and substituted into the hydraulic condition simulation submodule to recalculate the pressure / flow distribution of the entire pipeline network. The output results are the flow rate, velocity, and head loss of each pipe segment. The pressure and free head of each node can be directly linked to GIS map visualization; The maintenance route optimization submodule includes planning the shortest inspection route for maintenance personnel based on the improved Dijkstra algorithm, GIS coordinates of maintenance points, priority weights of maintenance points, and traffic restriction information in the GIS road layer. The pipeline expansion optimization submodule calculates the optimal pipeline expansion scheme based on a cost-benefit model; it determines the expansion scheme based on historical leakage data and maintenance costs, and updates the expanded pipeline topology data to the GIS data. The system management module includes setting corresponding operation permissions for different operators and setting up a data maintenance database.

2. The GIS-based water supply network management system according to claim 1, characterized in that, The method for locating potential leaks in the pipeline network based on pressure-flow coupling analysis includes: establishing a probability index P(x,y); Where (x,y) are the GIS coordinates of the area to be detected, and ΔP(x,y) represents the difference between the actual flow rate and the normal flow rate at the detection point. This represents the regional average normal pressure. Let ΔQ(x,y) represent the average normal flow rate for the region, and let ΔQ(x,y) represent the difference between the actual pressure and the normal pressure at the detection point. , The weighting coefficient is dynamically adjusted based on the pipeline material. A water leakage alarm is triggered when P(x,y)>0.8, and the candidate area of ​​the landing point is output in combination with GIS coordinates.

3. The GIS-based water supply network management system according to claim 1, characterized in that, Based on the node-segment model, the pressure and flow distribution of the pipeline network under different operating conditions are simulated to assist in the evaluation of the network's carrying capacity, including: calculating the head loss of the pipe segment using the Hardy-Cross method. , , Where Q is the flow rate of the pipe section, n is the flow index (n=2 for turbulent flow), and k is the resistance coefficient; A flow balance equation is constructed based on the premise that the sum of the inflows to any node equals the sum of the outflows. ,in, The flow rate in the pipe segment flowing into node i is positive when flowing into the node and negative when flowing out. q represents the user's water consumption, and m represents the number of nodes. The flow rate in the pipe segment is corrected through an iterative algorithm until the node flow balance error is < 0.01 m³ / s, at which point the result converges. When a leak is predicted, the leak is considered an abnormal node and substituted into the node flow balance equation to recalculate the pressure / flow distribution of the entire pipe network.

4. The GIS-based water supply network management system according to claim 1, characterized in that, Based on the improved Dijkstra algorithm, the shortest inspection route for maintenance personnel is planned, including calculating the comprehensive cost of the route C(i,j). C(i,j)=γd(i,j)+(1-γ)t(i,j)w: Where d(i,j) is the straight-line distance from node i to j calculated based on GIS coordinates, t(i,j) is the travel time between the road segments, w is the priority weight of the maintenance point, and γ is the distance weight coefficient. The node with the lowest cost is selected to plan the path. When γ=0.6, the distance is shortened first, and the starting point is the GIS coordinates of the maintenance center. The constraint is to avoid the construction section. The output is the optimal path order.

5. The GIS-based water supply network management system according to claim 1, characterized in that, Based on the cost-benefit model, the optimal pipeline expansion scheme is calculated as follows: Calculate the objective function to maximize net benefit NB: NB = ,in, For the water supply benefits in year t, Let r be the cost in year t, r be the discount rate, and T be the design life of the pipeline network.

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