Sewage pipe network alignment design method and system

Abstract

The invention discloses a sewage pipe network alignment design method and system, and the method comprises the steps: obtaining geographic data, geological data, hydrological data and building data of a peripheral region of a to-be-built sewage treatment station, and building a three-dimensional space constraint model according to multi-source data; in the three-dimensional space constraint model, according to the position information of the sewage treatment station, a Dijkstra algorithm is adopted to generate a main pipe network, branch pipe networks are correspondingly generated according to the main pipe network, and a topological structure of the sewage pipe network is obtained; performing flow field simulation on the topological structure of the sewage pipe network according to a preset condition, and outputting flow field characteristic data; key feature data are extracted, pipe diameter-burial depth-flow velocity multi-objective optimization is carried out according to the key feature data, and a target topological structure of the sewage pipe network is obtained. The method disclosed by the invention aims to obtain a globally optimal solution among the flow velocity requirement, the construction cost and the long-term operation and maintenance stability, so that multiple bottlenecks of a traditional design method in efficiency, precision and economy are broken through.

Description

Technical Field

[0001] The present invention relates to the technical field of pipeline design, and in particular to a sewage pipe network route design method and system. Background Art

[0002] With the acceleration of urbanization and rising environmental protection requirements, sewage pipe network systems, as a core component of urban infrastructure, face a direct impact on sewage treatment efficiency, construction costs, and sustainable operations and maintenance through scientific design and planning. Traditional sewage pipe network routing design relies heavily on manual experience and two-dimensional planar data, making it difficult to fully integrate multiple constraints such as geography, geology, hydrology, and the built environment. This can lead to redundancy in pipe network layouts, unreasonable burial depths, or substandard hydraulic conditions. Especially in complex terrain and densely built-up areas, empirical design can easily lead to pipe network siltation, uneven flow rates, and construction cost overruns. A data-driven, intelligently optimized design approach is urgently needed to improve the overall efficiency of pipe network systems.

[0003] While existing technologies for 3D modeling and algorithm optimization have been gradually applied to pipe network design, they still have significant limitations. For example, the construction of 3D spatial constraint models often lacks the deep integration of multi-source heterogeneous data (such as geological permeability and building underground structures), resulting in insufficient model accuracy. Pipeline network topology generation often uses algorithms with a single objective (such as the shortest path), ignoring the coordinated optimization of pipe diameter, burial depth, and flow velocity, which can easily lead to an imbalance between hydraulic performance and construction economics. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the purpose of the present invention is to provide a sewage pipe network route design method and system, aiming to achieve a global optimal solution between flow rate requirements, construction costs and long-term operation and maintenance stability, thereby breaking through the multiple bottlenecks of traditional design methods in efficiency, accuracy and economy.

[0005] A first aspect of the present invention is to provide a sewage pipe network alignment design method, the method comprising:

[0006] Obtain geographic data, geological data, hydrological data, and architectural data for the surrounding area of ​​the proposed sewage treatment site, and establish a three-dimensional spatial constraint model based on multi-source data;

[0007] In the three-dimensional spatial constraint model, a trunk pipe network is generated according to the location information of the sewage treatment site using the Dijkstra algorithm, and a branch pipe network is generated according to the trunk pipe network to obtain a topological structure of the sewage pipe network;

[0008] Performing flow field simulation on the topological structure of the sewage pipe network according to preset conditions, and outputting flow field characteristic data corresponding to the sewage pipe network;

[0009] At least part of the key characteristic data in the flow field characteristic data is extracted, and a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed based on the key characteristic data to obtain a target topological structure of the sewage pipe network.

[0010] According to one aspect of the above technical solution, within the three-dimensional spatial constraint model, based on the location information of the sewage treatment site, a trunk pipe network is generated using the Dijkstra algorithm, and a branch pipe network is generated corresponding to the trunk pipe network to obtain the topological structure of the sewage pipe network, including the following steps:

[0011] In the three-dimensional spatial constraint model, according to the location information of the sewage treatment site, a trunk pipeline network is generated by using the Dijkstra algorithm combined with an obstacle penetration penalty coefficient and a terrain adaptability weight;

[0012] Dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas based on the main pipeline network;

[0013] Using the Dijkstra algorithm, combined with the obstacle penetration penalty coefficient and the terrain adaptability weight, a branch pipeline network connected to the main pipeline network is generated in at least part of the sub-area;

[0014] Among them, the branch pipeline network connected to the main pipeline network includes branch pipeline networks that are directly connected or indirectly connected to the main pipeline network.

[0015] According to one aspect of the above technical solution, the step of dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas with reference to the main pipeline network includes:

[0016] Dividing the peripheral area of ​​the sewage treatment site into multiple functional areas using the main pipeline network as a dividing line;

[0017] Each functional area is divided into a plurality of polygons corresponding to the terrain contour, thereby obtaining a plurality of sub-areas respectively located on both sides of the main pipeline network.

[0018] According to one aspect of the above technical solution, the step of generating a branch pipeline network connected to the main pipeline network in at least part of the sub-area by using the Dijkstra algorithm in combination with the obstacle penetration penalty coefficient and the terrain adaptability weight includes:

[0019] The Dijkstra algorithm is used to combine the obstacle penetration penalty coefficient and the terrain fitness weight to score the multiple vertices of each polygon and obtain the vertex score corresponding to each vertex;

[0020] The vertex with the highest vertex score in each polygon is determined as the feature vertex, and multiple feature vertices of multiple adjacent polygons within a preset range are connected in sequence to obtain a branch pipeline network connected to the main pipeline network.

[0021] According to one aspect of the above technical solution, the steps of extracting at least part of the key feature data from the flow field feature data, performing multi-objective optimization of pipe diameter, burial depth, and flow velocity based on the key feature data, and obtaining a target topological structure of the sewage pipe network include:

[0022] Extracting at least part of the key characteristic data from the flow field characteristic data, including flow velocity data of each section of each branch pipe network;

[0023] The pipe diameter data and burial depth data corresponding to each branch pipe network are obtained, and combined with the flow velocity data of each section of each branch pipe network, a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed on each branch pipe network to obtain the target topological structure of the sewage pipe network.

[0024] According to one aspect of the above technical solution, the steps of obtaining the pipe diameter data and burial depth data corresponding to each branch pipe network, combining the flow velocity data of each section of each branch pipe network, and performing a multi-objective optimization of pipe diameter, burial depth, and flow velocity on each branch pipe network to obtain the target topology of the sewage pipe network include:

[0025] Obtain the pipe diameter and burial depth data corresponding to each section of each branch pipe network;

[0026] Combined with the flow velocity data of each section of each branch network, the pipe diameter and / or burial depth between at least two characteristic vertices in any branch network are adjusted to perform multi-objective optimization of the branch network based on pipe diameter, burial depth, and flow velocity.

[0027] Obtain the target topology of the sewage network.

[0028] According to one aspect of the above technical solution, the pipe diameter and / or burial depth between at least two characteristic vertices in any branch and trunk pipe network are adjusted, including adjusting the pipe diameter and / or burial depth between two adjacent characteristic vertices, and adjusting the pipe diameter and / or burial depth between two non-adjacent characteristic vertices.

[0029] A second aspect of the present invention is to provide a sewage pipe network alignment design system, which is applied to the method described in the above technical solution, and the system comprises:

[0030] The constraint modeling unit is used to obtain geographic data, geological data, hydrological data, and architectural data of the peripheral area of ​​the sewage treatment site to be built, and to establish a three-dimensional spatial constraint model based on the multi-source data;

[0031] A topology generation module is used to generate a trunk pipe network in the three-dimensional spatial constraint model according to the location information of the sewage treatment site using the Dijkstra algorithm, and generate a branch pipe network corresponding to the trunk pipe network to obtain a topological structure of the sewage pipe network;

[0032] A flow field simulation module, used to perform flow field simulation on the topological structure of the sewage pipe network according to preset conditions and output flow field characteristic data corresponding to the sewage pipe network;

[0033] The topology optimization module is used to extract at least part of the key characteristic data from the flow field characteristic data, perform multi-objective optimization of pipe diameter-burial depth-flow velocity based on the key characteristic data, and obtain the target topology structure of the sewage pipe network.

[0034] A third aspect of the present invention is to provide a readable storage medium having a computer program stored thereon, which implements the method described in the above technical solution when executed by a processor.

[0035] The fourth aspect of the present invention is an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the above technical solution when executing the computer program.

[0036] Compared with the prior art, the sewage pipe network alignment design method of the present invention has the following beneficial effects:

[0037] The present invention obtains geographic data, geological data, hydrological data, and architectural data of the peripheral area of ​​a sewage treatment station to be built, and establishes a three-dimensional spatial constraint model based on multi-source data; within the three-dimensional spatial constraint model, a main pipeline network is generated based on the location information of the sewage treatment station using the Dijkstra algorithm, and a branch pipeline network is generated corresponding to the main pipeline network to obtain the topological structure of the sewage pipeline network; a flow field simulation is performed on the topological structure of the sewage pipeline network according to preset conditions, and flow field characteristic data corresponding to the sewage pipeline network is output; at least part of the key characteristic data in the flow field characteristic data is extracted, and a multi-objective optimization of pipe diameter, burial depth, and flow velocity is performed based on the key characteristic data to obtain the target topological structure of the sewage pipeline network. The present invention can quickly generate the topological structure of the sewage pipeline network based on the multi-source data of the sewage treatment area of ​​the sewage treatment station, and perform multi-objective optimization to obtain the target topological structure, which is conducive to accurately guiding the construction of the sewage pipeline network, ensuring that the operating efficiency of the sewage pipeline network is at a high level to ensure pollution control efficiency, and can effectively avoid the need to rectify the sewage pipeline network in a short period of time and avoid the waste of resources caused by duplicate construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0039] Figure 1 Schematic diagram of the flow of a sewage pipe network routing design method according to one embodiment of the present invention;

[0040] Figure 2 Schematic diagram of the structure of a sewage pipe network routing design system in one embodiment of the present invention. DETAILED DESCRIPTION

[0041] To make the objectives, features, and advantages of the present invention more readily apparent, the following detailed description of specific embodiments of the present invention is provided in conjunction with the accompanying drawings. The accompanying drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0043] Example 1

[0044] See also Figure 1 The first embodiment of the present invention provides a sewage pipe network alignment design method, the method comprising steps S10 to S40:

[0045] Step S10 , obtaining geographic data, geological data, hydrological data and architectural data of the peripheral area of ​​the sewage treatment site to be built, and establishing a three-dimensional spatial constraint model based on the multi-source data.

[0046] First of all, it should be noted that the sewage pipe network routing design method shown in this embodiment is used to design the routing of the pipe network of the sewage treatment site to be built. Sewage treatment sites are usually set up in areas with relatively sparse populations or more sewage sources, such as in the suburbs of the city and industrial parks, so as to minimize the interference with the normal lives of residents.

[0047] Sewage treatment plants are typically used to treat wastewater generated by urban life and industrial production. Therefore, they must be connected to various sewage outlets through pipes to form a sewage pipe network. This allows sewage to quickly enter the sewage treatment plant through the sewage pipe network for treatment, and then be discharged into rivers after pollution control. Therefore, a well-designed sewage pipe network can effectively improve pollution control efficiency.

[0048] In this embodiment, when designing the sewage pipe network route, the geographic data, geological data, hydrological data and building data of the peripheral area of ​​the sewage treatment site to be built, that is, the building distribution data, will be obtained first to constitute multi-source data. Then, a three-dimensional spatial constraint model will be constructed based on the multi-source data. The three-dimensional spatial constraint model will be used to limit the design boundary of the sewage pipe network, making the topological structure design of the sewage pipe network more reasonable, thereby improving the pollution control efficiency.

[0049] Step S20: In the three-dimensional spatial constraint model, a trunk pipe network is generated using the Dijkstra algorithm according to the location information of the sewage treatment site, and a branch pipe network is generated corresponding to the trunk pipe network to obtain a topological structure of the sewage pipe network.

[0050] In this embodiment, within the three-dimensional spatial constraint model, the Dijkstra algorithm is used to generate a trunk pipe network based on the location information of the sewage treatment site, and a branch pipe network is generated according to the trunk pipe network to obtain the topological structure of the sewage pipe network, including the following steps:

[0051] In the three-dimensional spatial constraint model, according to the location information of the sewage treatment site, a trunk pipeline network is generated by using the Dijkstra algorithm combined with an obstacle penetration penalty coefficient and a terrain adaptability weight;

[0052] Dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas based on the main pipeline network;

[0053] Using the Dijkstra algorithm, combined with the obstacle penetration penalty coefficient and the terrain adaptability weight, a branch pipeline network connected to the main pipeline network is generated in at least part of the sub-area;

[0054] Among them, the branch pipeline network connected to the main pipeline network includes branch pipeline networks that are directly connected or indirectly connected to the main pipeline network.

[0055] Specifically, before designing the topology of the sewage pipe network, the location information of the sewage treatment site will be obtained first, including the latitude and longitude information of the sewage treatment site, as well as the geographical information of the sewage treatment site. The Dijkstra algorithm is used in combination with the obstacle penetration penalty coefficient and the terrain adaptability weight to generate the trunk pipe network directly connected to the sewage treatment site. The number, density and length of the trunk pipe network depend on the pollution control range of the sewage treatment site. For example, if the pollution control range is 10km 2Then, according to the number and distribution of pollution sources within the pollution control range, a corresponding trunk pipeline network is set up. There can be multiple trunk pipelines, and multiple trunk pipelines are directly connected to the sewage treatment station. Then, the pollution control range, that is, the peripheral area, is divided into multiple sub-areas, which are usually divided according to the area and pollution discharge density. For example, the sub-area corresponding to the area with a relatively concentrated population and residential area is smaller, while the area of ​​the sub-area can be appropriately expanded in the area with a sparse population and residential area. Then, in at least part of the sub-areas, a branch pipeline network connected to the adjacent trunk pipeline network is generated. There are usually multiple branch pipelines connected to the trunk pipeline network, thereby obtaining the topological structure of the sewage pipeline network.

[0056] For example, the sewage treatment site shown in this embodiment is located at point S in the northwest corner of an industrial park, and is responsible for the pollution control of all enterprises in the industrial park. Then, based on the location information of point S where the sewage treatment site is located and the enterprise distribution information related to the industrial park, at least one main pipeline network is first generated, for example, including a, b, and c main pipeline networks, which correspond to different A, B, and C functional areas in the industrial park, respectively. That is, the a, b, and c main pipeline networks extend to different A, B, and C functional areas in the industrial park, respectively. Then, multiple branch pipeline networks corresponding to the a, b, and c main pipeline networks are generated in the A, B, and C functional areas, respectively. Each branch pipeline network can collect industrial wastewater output from multiple sewage sources, so that the industrial wastewater is concentrated to the a, b, and c main pipeline networks through multiple branch pipeline networks and then transported to the sewage treatment site at point S, and finally effectively treated through the sewage treatment site.

[0057] In this embodiment, the steps of dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas with reference to the main pipeline network include:

[0058] Dividing the peripheral area of ​​the sewage treatment site into multiple functional areas using the main pipeline network as a dividing line;

[0059] Each functional area is divided into a plurality of polygons corresponding to the terrain contour, thereby obtaining a plurality of sub-areas respectively located on both sides of the main pipeline network.

[0060] Specifically, in this embodiment, the main pipeline network is used as the dividing line to divide the peripheral area of ​​the sewage treatment site, that is, the pollution control area, into multiple functional areas. For example, the industrial park is divided into functional area A, functional area B, and functional area C. A main pipeline network is generated for each functional area, and then each functional area is divided into multiple polygons corresponding to the terrain contour, obtaining multiple sub-areas located on both sides of the main pipeline network. Each sub-area corresponds to a branch pipeline network connected to the main pipeline network in this functional area.

[0061] In this embodiment, the Dijkstra algorithm is used, combined with the obstacle penetration penalty coefficient and the terrain adaptability weight, to generate a branch pipeline network connected to the main pipeline network in at least part of the sub-area, including:

[0062] The Dijkstra algorithm is used to combine the obstacle penetration penalty coefficient and the terrain fitness weight to score the multiple vertices of each polygon and obtain the vertex score corresponding to each vertex;

[0063] The vertex with the highest vertex score in each polygon is determined as the feature vertex, and multiple feature vertices of multiple adjacent polygons within a preset range are connected in sequence to obtain a branch pipeline network connected to the main pipeline network.

[0064] Specifically, the Dijkstra algorithm is used, combined with the obstacle penetration penalty coefficient and the terrain fitness weight, to perform value scoring on each sub-area, that is, the multiple vertices of the corresponding polygon, and obtain the vertex score corresponding to each vertex. The so-called vertex is the multiple edge points of the terrain contour where the sub-area is located, which is mainly used to set up a common sewage collection outlet on the branch pipeline network according to the vertex position. For example, the A1, A2 and A3 plots in the A sub-area correspond to the areas where the three factories are located respectively. The feature vertex is determined by selecting the vertex with the highest vertex score, that is, a common sewage collection point opened on the branch pipeline network is determined in the A1, A2 and A3 plots, and then the multiple feature vertices of the multiple polygons adjacent in sequence within the preset range are connected in sequence, for example, 1km 2 The five characteristic vertices of the five adjacent polygons along a certain road are connected in sequence to obtain one of the branch pipeline networks connected to the main pipeline network.

[0065] It should be noted here that the purpose of sub-area division in this embodiment includes reasonably setting the approximate direction of the branch and trunk pipeline network according to the distribution status of multiple sewage sources, which can effectively increase the sewage flow rate to improve the pollution control efficiency, save pipeline materials to a certain extent, and shorten the construction period.

[0066] Step S30 , performing flow field simulation on the topological structure of the sewage pipe network according to preset conditions, and outputting flow field characteristic data corresponding to the sewage pipe network.

[0067] In this embodiment, after the topological structure of the sewage pipe network is preliminarily constructed, it is also necessary to obtain the sewage discharge data of the sewage source, that is, the sewage discharge subject, including the discharge volume, sewage type, etc., and then combine historical meteorological data, such as flood season data, to perform flow field simulation on the topological structure of the sewage pipe network, and output the corresponding flow field characteristic data of the sewage pipe network. The flow field characteristic data can be used to determine whether the topological structure of the sewage pipe network is reasonable and whether it is necessary to modify the pipe network direction, pipe diameter, burial depth, flow rate, etc.

[0068] Step S40: extract at least part of the key characteristic data from the flow field characteristic data, perform multi-objective optimization of pipe diameter, burial depth and flow velocity based on the key characteristic data, and obtain a target topological structure of the sewage pipe network.

[0069] In this embodiment, after constructing the topological structure of the sewage pipe network and performing flow field simulation on it to obtain flow field characteristic data, at least part of the key characteristic data of the flow field characteristic data will be extracted, including the flow velocity of each main pipe network and branch pipe network, to determine whether sewage blockage, leakage, etc. will occur under the corresponding flow velocity. Then, based on the key characteristic data, a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed on several main pipe networks and their connected branch pipe networks to obtain the target topological structure of the sewage pipe network. Finally, the corresponding arrangement of the sewage pipe network is carried out based on the target topological structure to complete the construction of the sewage pipe network.

[0070] For example, when the sewage discharge rate between plots A1, A2 and A3 in sub-area A does not match the sewage collection rate of the branch network, and there is a slow flow rate, the relevant topological structure of the branch network is obtained to determine whether the diameter of the branch network is too small and whether the burial depth is appropriate. For example, the diameter of the branch network is appropriately increased in the topological structure of the sewage network, and then the flow field simulation is performed again to verify whether the optimization method has achieved the corresponding purpose. If the sewage collection and discharge rates of all main pipelines and all branch pipelines match each other, it is determined that the optimization has achieved the corresponding purpose, and finally the target topological structure of the sewage network is obtained.

[0071] Compared with the prior art, the sewage pipe network alignment design method shown in this embodiment has the following beneficial effects:

[0072] This embodiment obtains geographic data, geological data, hydrological data, and architectural data for the peripheral area of ​​a sewage treatment station to be constructed, and establishes a three-dimensional spatial constraint model based on multi-source data. Within the three-dimensional spatial constraint model, a main pipeline network is generated using the Dijkstra algorithm based on the location information of the sewage treatment station, and a branch pipeline network is generated corresponding to the main pipeline network to obtain the topological structure of the sewage pipeline network. A flow field simulation is performed on the topological structure of the sewage pipeline network according to preset conditions, and flow field characteristic data corresponding to the sewage pipeline network is output. At least a portion of the key characteristic data in the flow field characteristic data is extracted, and a multi-objective optimization of pipe diameter, burial depth, and flow velocity is performed based on the key characteristic data to obtain the target topological structure of the sewage pipeline network. This embodiment can quickly generate the topological structure of the sewage pipeline network based on multi-source data of the sewage treatment station pollution control area, and perform multi-objective optimization on this to obtain the target topological structure, which is conducive to accurately guiding the construction of the sewage pipeline network, ensuring that the operating efficiency of the sewage pipeline network is at a high level to ensure pollution control efficiency, and effectively avoiding the need to rectify the sewage pipeline network in a short period of time, thereby avoiding the waste of resources caused by duplicate construction.

[0073] Example 2

[0074] The second embodiment of the present invention also provides a sewage pipe network top line design method. The sewage pipe network alignment design method shown in this embodiment is basically similar to the sewage pipe network alignment design method shown in the first embodiment, except that:

[0075] In this embodiment, the steps of extracting at least part of the key feature data from the flow field feature data, performing multi-objective optimization of pipe diameter, burial depth, and flow velocity based on the key feature data, and obtaining a target topological structure of the sewage pipe network include:

[0076] Extracting at least part of the key characteristic data from the flow field characteristic data, including flow velocity data of each section of each branch pipe network;

[0077] The pipe diameter data and burial depth data corresponding to each branch pipe network are obtained, and combined with the flow velocity data of each section of each branch pipe network, a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed on each branch pipe network to obtain the target topological structure of the sewage pipe network.

[0078] The steps of obtaining the pipe diameter data and burial depth data corresponding to each branch pipe network, combining the flow velocity data of each section of each branch pipe network, and performing multi-objective optimization of pipe diameter, burial depth, and flow velocity on each branch pipe network to obtain the target topological structure of the sewage pipe network include:

[0079] Obtain the pipe diameter and burial depth data corresponding to each section of each branch pipe network;

[0080] Combined with the flow velocity data of each section of each branch network, the pipe diameter and / or burial depth between at least two characteristic vertices in any branch network are adjusted to perform multi-objective optimization of the branch network based on pipe diameter, burial depth, and flow velocity.

[0081] Obtain the target topology of the sewage network.

[0082] Furthermore, the pipe diameter and / or burial depth between at least two characteristic vertices in any branch pipe network are adjusted, including adjusting the pipe diameter and / or burial depth between two adjacent characteristic vertices, and adjusting the pipe diameter and / or burial depth between two non-adjacent characteristic vertices.

[0083] Specifically, in this embodiment, after the flow field simulation of the topological structure of the sewage pipe network is performed to output the flow field characteristic data, the flow velocity data of each section of each branch pipe network in the flow field characteristic data is extracted as the key characteristic data of the flow field characteristic data, and then the pipe diameter data and burial depth data of each branch pipe network are obtained according to the topological structure. Combined with the flow velocity data of each section of the pipe network in each branch pipe network, a multi-objective optimization of pipe diameter-burial depth-flow velocity is performed on each branch pipe network. Specifically, the pipe diameter and / or burial depth of the pipe network between at least two characteristic vertices in any branch pipe network, that is, the two common sewage collection outlets, are adjusted, for example, the pipe diameter of the pipe network is increased or decreased, the buried depth of the pipe network, the buried depth angle, etc., to achieve multi-objective optimization of pipe diameter-buried depth and flow velocity in the branch pipe network, and obtain the target topological structure of the sewage pipe network to guide the construction of the sewage pipe network.

[0084] Example 3

[0085] See also Figure 2 A third embodiment of the present invention provides a sewage pipe network alignment design system, which is applied to the method described in any of the above embodiments, and the system includes:

[0086] The constraint modeling unit 10 is used to obtain geographic data, geological data, hydrological data and architectural data of the peripheral area of ​​the sewage treatment site to be built, and establish a three-dimensional spatial constraint model based on the multi-source data;

[0087] A topology generation module 20 is configured to generate a trunk pipe network within the three-dimensional spatial constraint model based on the location information of the sewage treatment site using the Dijkstra algorithm, and generate branch pipe networks corresponding to the trunk pipe network to obtain a topological structure of the sewage pipe network;

[0088] A flow field simulation module 30 is used to perform flow field simulation on the topological structure of the sewage pipe network according to preset conditions and output flow field characteristic data corresponding to the sewage pipe network;

[0089] The topology optimization module 40 is used to extract at least part of the key characteristic data from the flow field characteristic data, and perform multi-objective optimization of pipe diameter-burial depth-flow velocity based on the key characteristic data to obtain the target topology structure of the sewage pipe network.

[0090] Compared with the prior art, the sewage pipe network routing design system shown in this embodiment has the following beneficial effects:

[0091] This embodiment obtains geographic data, geological data, hydrological data, and architectural data for the peripheral area of ​​a sewage treatment station to be constructed, and establishes a three-dimensional spatial constraint model based on multi-source data. Within the three-dimensional spatial constraint model, a main pipeline network is generated using the Dijkstra algorithm based on the location information of the sewage treatment station, and a branch pipeline network is generated corresponding to the main pipeline network to obtain the topological structure of the sewage pipeline network. A flow field simulation is performed on the topological structure of the sewage pipeline network according to preset conditions, and flow field characteristic data corresponding to the sewage pipeline network is output. At least a portion of the key characteristic data in the flow field characteristic data is extracted, and a multi-objective optimization of pipe diameter, burial depth, and flow velocity is performed based on the key characteristic data to obtain the target topological structure of the sewage pipeline network. This embodiment can quickly generate the topological structure of the sewage pipeline network based on multi-source data of the sewage treatment station pollution control area, and perform multi-objective optimization on this to obtain the target topological structure, which is conducive to accurately guiding the construction of the sewage pipeline network, ensuring that the operating efficiency of the sewage pipeline network is at a high level to ensure pollution control efficiency, and effectively avoiding the need to rectify the sewage pipeline network in a short period of time, thereby avoiding the waste of resources caused by duplicate construction.

[0092] Example 4

[0093] A fourth embodiment of the present invention provides a readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method described in any one of the above embodiments is implemented.

[0094] Example 5

[0095] A fifth embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any one of the above embodiments when executing the computer program.

[0096] Throughout this specification, references to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. Throughout this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0097] The above-described embodiments merely illustrate several implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A sewage pipe network alignment design method, characterized in that: The method comprises: Obtain geographic data, geological data, hydrological data, and architectural data for the surrounding area of ​​the proposed sewage treatment site, and establish a three-dimensional spatial constraint model based on this multi-source data; In the three-dimensional spatial constraint model, a trunk pipe network is generated according to the location information of the sewage treatment site using the Dijkstra algorithm, and a branch pipe network is generated according to the trunk pipe network to obtain a topological structure of the sewage pipe network; Performing flow field simulation on the topological structure of the sewage pipe network according to preset conditions, and outputting flow field characteristic data corresponding to the sewage pipe network; At least part of the key characteristic data in the flow field characteristic data is extracted, and a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed based on the key characteristic data to obtain a target topological structure of the sewage pipe network.

2. The sewage pipe network alignment design method according to claim 1, characterized in that: The steps of generating a trunk pipe network using the Dijkstra algorithm according to the location information of the sewage treatment site within the three-dimensional spatial constraint model, generating a branch pipe network corresponding to the trunk pipe network, and obtaining a topological structure of the sewage pipe network include: In the three-dimensional spatial constraint model, according to the location information of the sewage treatment site, a trunk pipeline network is generated by using the Dijkstra algorithm combined with an obstacle penetration penalty coefficient and a terrain adaptability weight; Dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas based on the main pipeline network; Using the Dijkstra algorithm, combined with the obstacle penetration penalty coefficient and the terrain adaptability weight, a branch pipeline network connected to the main pipeline network is generated in at least part of the sub-area; Among them, the branch pipeline network connected to the main pipeline network includes branch pipeline networks that are directly connected or indirectly connected to the main pipeline network.

3. The sewage pipe network alignment design method according to claim 2, characterized in that: The step of dividing the peripheral area of ​​the sewage treatment site into multiple sub-areas with reference to the main pipeline network includes: Dividing the peripheral area of ​​the sewage treatment site into multiple functional areas using the main pipeline network as a dividing line; Each functional area is divided into a plurality of polygons corresponding to the terrain contour, thereby obtaining a plurality of sub-areas respectively located on both sides of the main pipeline network.

4. The sewage pipe network alignment design method according to claim 3, characterized in that: The step of generating a branch pipeline network connected to the main pipeline network in at least part of the sub-area by using the Dijkstra algorithm in combination with the obstacle penetration penalty coefficient and the terrain adaptability weight includes: The Dijkstra algorithm is used to combine the obstacle penetration penalty coefficient and the terrain fitness weight to score the multiple vertices of each polygon and obtain the vertex score corresponding to each vertex; The vertex with the highest vertex score in each polygon is determined as the feature vertex, and multiple feature vertices of multiple adjacent polygons within a preset range are connected in sequence to obtain a branch pipeline network connected to the main pipeline network.

5. The sewage pipe network alignment design method according to any one of claims 1 to 4, characterized in that: The steps of extracting at least part of the key characteristic data from the flow field characteristic data, performing multi-objective optimization of pipe diameter, burial depth and flow velocity based on the key characteristic data, and obtaining a target topological structure of the sewage pipe network include: Extracting at least part of the key characteristic data from the flow field characteristic data, including flow velocity data of each section of each branch pipe network; The pipe diameter data and burial depth data corresponding to each branch pipe network are obtained, and combined with the flow velocity data of each section of each branch pipe network, a multi-objective optimization of pipe diameter, burial depth and flow velocity is performed on each branch pipe network to obtain the target topological structure of the sewage pipe network.

6. The sewage pipe network alignment design method according to claim 5, characterized in that: The steps of obtaining the pipe diameter data and burial depth data corresponding to each branch pipe network, combining the flow velocity data of each pipe section in each branch pipe network, and performing multi-objective optimization of pipe diameter, burial depth, and flow velocity on each branch pipe network to obtain the target topology structure of the sewage pipe network include: Obtain the pipe diameter and burial depth data corresponding to each section of each branch pipe network; Combined with the flow velocity data of each section of each branch network, the pipe diameter and / or burial depth between at least two characteristic vertices in any branch network are adjusted to perform multi-objective optimization of the branch network based on pipe diameter, burial depth, and flow velocity. Obtain the target topology of the sewage network.

7. The sewage pipe network alignment design method according to claim 6, characterized in that: Adjust the pipe diameter and / or burial depth between at least two characteristic vertices in any branch and trunk pipe network, including adjusting the pipe diameter and / or burial depth between two adjacent characteristic vertices, and adjusting the pipe diameter and / or burial depth between two non-adjacent characteristic vertices.

8. A sewage pipe network routing design system, characterized in that: The method according to any one of claims 1 to 7, wherein the system comprises: The constraint modeling unit is used to obtain geographic data, geological data, hydrological data, and architectural data of the peripheral area of ​​the sewage treatment site to be built, and to establish a three-dimensional spatial constraint model based on the multi-source data; A topology generation module is used to generate a trunk pipe network in the three-dimensional spatial constraint model according to the location information of the sewage treatment site using the Dijkstra algorithm, and generate a branch pipe network corresponding to the trunk pipe network to obtain a topological structure of the sewage pipe network; A flow field simulation module, used to perform flow field simulation on the topological structure of the sewage pipe network according to preset conditions and output flow field characteristic data corresponding to the sewage pipe network; The topology optimization module is used to extract at least part of the key characteristic data from the flow field characteristic data, perform multi-objective optimization of pipe diameter-burial depth-flow velocity based on the key characteristic data, and obtain the target topology structure of the sewage pipe network.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

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