Pipeline network breakpoint automatic identification method, device, equipment, medium and product
By building an undirected graph of the pipeline network and the shortest path algorithm to automatically identify breakpoints, the problems of low efficiency and high cost of manual breakpoint recognition are solved, and efficient and accurate pipeline network breakpoint recognition is achieved.
Patent Information
- Application Number
- CN202411217710.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-02
- Publication Date
- 2024-12-31
AI Technical Summary
In the prior art, manual identification of pipeline network breakpoints has problems such as strong subjectivity, low efficiency and high labor costs.
By constructing an undirected graph based on the location information of the pipeline network, determining the clustering situation, and automatically identifying pipeline network breakpoints using the shortest path algorithm, reducing the dependence of manual identification.
It improves the accuracy and efficiency of identification of pipeline network breakpoints, reduces labor costs, and increases efficiency by 10 times compared with the existing technology, and reduces cost by 40%.
Smart Images
Figure CN119227282A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of communication technology, and in particular to a method, device, equipment, medium and product for automatically identifying pipeline network breakpoints. Background Art
[0002] With the development of cities and the improvement of people's living standards, the requirements for urban beauty and environmental quality are also increasing. Overhead network cables often have phenomena such as random connection and pulling, borrowing poles to lay wires, cross-street connections, overloaded wires, and tilted poles. These problems not only affect the safety of power supply, have an adverse impact on the lives of residents, but also seriously damage the city's landscape and image. Therefore, it has become an important measure to ensure power supply safety and enhance the image of the city by putting overhead network cables underground and connecting users through pipeline networks. With the acceleration of urbanization, land resources are becoming increasingly tight. Replacing overhead network cables with pipeline network cables can also make more effective use of land resources and provide support for the sustainable development of cities. In addition, the service life of pipeline network cables is greatly extended compared to overhead network cables, reducing the maintenance and replacement costs caused by line aging and damage, and improving the economic benefits of communication operators.
[0003] As more and more pipelines are being built, pipelines in large and medium-sized cities have been connected into a network. However, there may be breakpoints between pipeline networks that have been built in batches over the years. Because the conditions at the time did not allow construction at rivers, bridges, and railways, the pipeline network was interrupted, i.e., breakpoints were formed. These breakpoints affect the availability and connectivity of the pipeline network, greatly reducing the efficiency of the use of the pipeline network. In recent years, operators have begun to search and rectify these "pipeline network breakpoints", but most of the existing technologies use manual methods to identify the breakpoints of the pipeline network. At present, manual methods mainly rely on visual observation of pipeline maps to find breakpoints that may affect the connectivity of the pipeline network based on experience.
[0004] Although there are written standards and guidance methods for manually identifying pipeline network breakpoints, there are still problems of strong subjectivity and low efficiency. In addition, as the pipeline network is constantly being built, new breakpoints will appear. Manual judgment can only be repeated by multiple people observing the pipeline diagram, which has a high labor cost. Summary of the invention
[0005] The embodiments of the present application provide a method, device, equipment, medium and product for automatically identifying pipeline network breakpoints, which are used to solve the technical problems in the prior art of manually identifying pipeline network breakpoints, which are highly subjective, inefficient and have high labor costs, thereby improving accuracy and efficiency and reducing labor costs.
[0006] In a first aspect, an embodiment of the present application provides a method for automatically identifying breakpoints in a pipeline network, comprising the following steps.
[0007] Determine an undirected graph of a pipeline network based on location information of a plurality of pipeline networks; Based on the pipeline network undirected graph, determining the clustering conditions corresponding to all the pipeline networks; Based on the clustering situation, pipeline network breakpoints are determined.
[0008] In one embodiment, the pipeline network includes two pipe wells, and the pipe wells are end points of the pipeline network; The step of determining the pipeline network undirected graph based on the location information of the plurality of pipeline networks comprises: For each of the pipeline networks, a pipe well in the pipeline network is used as a node in a sub-undirected graph corresponding to the pipeline network; and a connection line between two pipe wells in the pipeline network is used as an edge in the sub-undirected graph; Based on the location information corresponding to all the sub-undirected graphs and all the pipe wells, the pipeline network undirected graph is determined.
[0009] In one embodiment, determining the pipeline network undirected graph based on the location information corresponding to all sub-undirected graphs and all pipe wells includes: Based on the corresponding position information of all the pipe wells, the sub-undirected graphs with the same pipe wells are connected to determine at least one cluster undirected graph; The pipeline network undirected graph is determined based on all cluster undirected graphs.
[0010] In one embodiment, the clustering situation includes a main cluster undirected graph and a branch cluster undirected graph, and determining the clustering situation corresponding to all the pipeline networks based on the pipeline network undirected graph includes: Based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the cluster undirected graph with the largest number of nodes is determined as a main cluster undirected graph, and the other cluster undirected graphs except the main cluster undirected graph are determined as branch cluster undirected graphs.
[0011] In one embodiment, determining the pipeline network breakpoint based on the clustering situation includes: For each of the branch cluster undirected graphs, based on the position information of each node corresponding to the branch cluster undirected graph and the position information of each node corresponding to the main cluster undirected graph, determine the shortest path from the branch cluster undirected graph to the main cluster undirected graph; The pipeline network breakpoints are determined based on the shortest paths.
[0012] In one embodiment, determining the pipeline network breakpoint based on each of the shortest paths includes: The shortest path that is smaller than a preset breakpoint threshold is determined as the pipeline network breakpoint.
[0013] In a second aspect, an embodiment of the present application provides an automatic identification device for pipeline network breakpoints, comprising the following modules.
[0014] An undirected graph module, used for determining an undirected graph of a pipeline network based on location information of a plurality of pipeline networks; A clustering module, used for determining the clustering conditions corresponding to all the pipeline networks based on the pipeline network undirected graph; The breakpoint module is used to determine the pipeline network breakpoint based on the clustering situation.
[0015] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory storing a computer program, wherein when the processor executes the computer program, the steps of the method for automatically identifying pipeline network breakpoints described in the first aspect are implemented.
[0016] In a fourth aspect, an embodiment of the present application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for automatically identifying pipeline network breakpoints described in the first aspect.
[0017] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method for automatically identifying pipeline network breakpoints as described in the first aspect.
[0018] The automatic identification method, device, equipment, medium and product of pipeline network breakpoints provided in the embodiments of the present application determine the pipeline network undirected graph based on the location information of multiple pipeline networks, and then determine the clustering conditions corresponding to all pipeline networks based on the pipeline network undirected graph. Further based on the clustering conditions, the pipeline network breakpoints are determined. The technical solution of the present invention does not require manual identification of pipeline network breakpoints, improves accuracy and identification efficiency, and reduces labor costs. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0020] Figure 1 It is a flow chart of the method for automatically identifying pipeline network breakpoints provided in an embodiment of the present application.
[0021] Figure 2 It is a schematic diagram of a sub-undirected graph provided in an embodiment of the present application.
[0022] Figure 3It is a schematic diagram of a cluster undirected graph provided in an embodiment of the present application.
[0023] Figure 4 It is a schematic diagram of an undirected graph of a pipeline network provided in an embodiment of the present application.
[0024] Figure 5 It is a structural schematic diagram of an automatic identification device for pipeline network breakpoints provided in an embodiment of the present application.
[0025] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0026] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0027] Figure 1 Schematic diagram of the process of the automatic identification method of pipeline network breakpoints provided in the embodiment of the present application. Figure 1 , an embodiment of the present application provides a method for automatically identifying pipeline network breakpoints, including the following steps 110 to 130.
[0028] Step 110: Determine an undirected graph of a pipeline network based on location information of a plurality of pipeline networks.
[0029] Specifically, first, the location information of multiple pipeline networks can be obtained, and the location information can be longitude and latitude information, and then the pipeline network undirected graph can be determined based on the location information of multiple pipeline networks. It is easy to understand that when the pipeline network and its location information change, the pipeline network undirected graph also changes accordingly.
[0030] In one embodiment, the pipeline network includes two pipe wells, and the pipe wells are end points of the pipeline network; The step of determining the pipeline network undirected graph based on the location information of the plurality of pipeline networks comprises: For each of the pipeline networks, a pipe well in the pipeline network is used as a node in a sub-undirected graph corresponding to the pipeline network; and a connection line between two pipe wells in the pipeline network is used as an edge in the sub-undirected graph; Based on the location information corresponding to all the sub-undirected graphs and all the pipe wells, the pipeline network undirected graph is determined.
[0031] Specifically, the pipeline network includes two pipe wells, and the pipe wells are endpoints of the pipeline network. It is easy to understand that the location information of the pipeline network can also be represented by the location information of the corresponding pipe wells.
[0032] Furthermore, for each pipeline network, the pipe wells in the pipeline network can be used as nodes in the sub-undirected graph corresponding to the pipeline network, and the connection between two pipe wells in the pipeline network can be used as edges in the sub-undirected graph. Figure 2 is a schematic diagram of a sub-undirected graph provided in an embodiment of the present application, with reference to Figure 2 , node 0 and node 1 are two pipe wells corresponding to the pipeline network. After determining the sub-undirected graphs corresponding to each pipeline network, the pipeline network undirected graph can be determined based on the location information corresponding to all sub-undirected graphs and all pipe wells.
[0033] In the above embodiment, the sub-undirected graphs corresponding to each pipeline network are first determined, and then the pipeline network undirected graph is determined according to the location information corresponding to all the sub-undirected graphs and all the pipe wells, which lays the foundation for the subsequent determination of the breakpoints of the pipeline network. In addition, the use of undirected graphs can intuitively display the connection between nodes and edges, making the complex relationship between pipeline networks easy to understand and analyze.
[0034] In one embodiment, determining the pipeline network undirected graph based on the location information corresponding to all sub-undirected graphs and all pipe wells includes: Based on the location information corresponding to all the pipe wells, the sub-undirected graphs with the same pipe wells are connected to determine at least one cluster undirected graph; The pipeline network undirected graph is determined based on all cluster undirected graphs.
[0035] Specifically, based on the location information corresponding to all the pipe wells, the sub-undirected graphs with the same pipe wells can be connected to determine at least one cluster undirected graph. It is easy to understand that the cluster undirected graph can represent the pipeline network with a connection relationship. For example, Figure 3 : is a schematic diagram of a cluster undirected graph provided in an embodiment of the present application. Node 0 and node 1 correspond to a sub-undirected graph A, and node 0 and node 2 correspond to a sub-undirected graph B. Since the sub-undirected graph A and the sub-undirected graph B have the same tube well (node 0), the sub-undirected graph A can be connected with the sub-undirected graph B. The obtained cluster undirected graph is as follows: Figure 3 shown.
[0036] Furthermore, the pipeline network undirected graph can be determined based on all cluster undirected graphs. For example, all cluster undirected graphs can be spliced and the spliced image can be determined as the pipeline network undirected graph. Figure 4 is a schematic diagram of an undirected graph of a pipeline network provided in an embodiment of the present application, with reference to Figure 4, nodes 0, 1 and 2 form a cluster undirected graph, nodes 3 and 4 form a cluster undirected graph, nodes 5, 6, 7 and 8 form a cluster undirected graph, and nodes 9 and 10 form a cluster undirected graph. Combining the above four cluster undirected graphs, we construct the following Figure 4 The pipeline network undirected graph shown is shown in FIG. It is easy to understand that this embodiment is for the convenience of explanation. Figure 4 The pipeline network undirected graph shown includes only 10 nodes, but in actual applications, there may be thousands or tens of thousands of nodes in a pipeline network undirected graph.
[0037] In the above embodiment, based on the corresponding location information of all pipe wells, the sub-undirected graphs with the same pipe wells are connected to determine at least one cluster undirected graph, and the pipeline network undirected graph is determined based on all cluster undirected graphs, so that the corresponding clustering of the pipeline network can be determined more reasonably based on the pipeline network undirected graph.
[0038] Step 120: Based on the pipeline network undirected graph, determine the clustering conditions corresponding to all the pipeline networks.
[0039] In one embodiment, the clustering situation includes a main cluster undirected graph and a branch cluster undirected graph, and determining the clustering situation corresponding to all the pipeline networks based on the pipeline network undirected graph includes: Based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the cluster undirected graph with the largest number of nodes is determined as a main cluster undirected graph, and the other cluster undirected graphs except the main cluster undirected graph are determined as branch cluster undirected graphs.
[0040] Specifically, although the pipeline network undirected graph includes at least one cluster undirected graph, that is, the pipeline network is divided into at least one cluster, in order to determine the power outage of the pipeline network, the cluster undirected graphs in the pipeline network graph can also be distinguished. The clustering corresponding to all pipeline networks may include a main cluster undirected graph and a branch cluster undirected graph. Based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the cluster undirected graph with the largest number of nodes can be determined as the main cluster undirected graph, and the other cluster undirected graphs except the main cluster undirected graph can be determined as branch cluster undirected graphs. Among them, the pipeline network corresponding to the main cluster undirected graph can represent the pipeline network with the widest coverage in a specific area.
[0041] For example, refer to Figure 4 , the cluster undirected graph composed of nodes 5, 6, 7 and 8 can be determined as the main cluster undirected graph, and the cluster undirected graph composed of nodes 0, 1 and 2, the cluster undirected graph composed of nodes 3 and 4, and the cluster undirected graph composed of nodes 9 and 10 can be determined as branch cluster undirected graphs.
[0042] Optionally, in the process of determining the clustering conditions corresponding to all pipeline networks based on the pipeline network undirected graph, the clustering can be processed in parallel on different computing devices to increase the clustering speed. In determining the main cluster undirected graph, the distance from each node in the main cluster undirected graph to the core computer room can also be considered to reduce communication overhead.
[0043] In the above embodiment, based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the clustering conditions corresponding to all pipeline networks are determined, so that the pipeline network breakpoints can be determined more conveniently according to the clustering conditions.
[0044] Step 130: Determine pipeline network breakpoints based on the clustering situation.
[0045] Specifically, the pipeline network breakpoints can be determined based on the clustering situation, and the pipeline network breakpoints are used to evaluate whether the pipeline networks are connected smoothly. The more pipeline network breakpoints there are, the greater the defects in the pipeline network construction, which will result in the phenomenon that although the user is connected to the pipeline network, he cannot connect to the entire communication network.
[0046] In one embodiment, determining the pipeline network breakpoint based on the clustering situation includes: For each of the branch cluster undirected graphs, based on the position information of each node corresponding to the branch cluster undirected graph and the position information of each node corresponding to the main cluster undirected graph, determine the shortest path from the branch cluster undirected graph to the main cluster undirected graph; The pipeline network breakpoints are determined based on the shortest paths.
[0047] Specifically, after determining the clustering of all pipeline networks, for each branch cluster undirected graph, the shortest path from the branch cluster undirected graph to the main cluster undirected graph can be determined based on the paths from each node corresponding to the branch cluster undirected graph to each node corresponding to the main cluster undirected graph. This process can be performed by the following methods (1) to (3).
[0048] Method (1): For each branch cluster undirected graph, based on the position information of each node corresponding to the branch cluster undirected graph and the position information of each node corresponding to the main cluster undirected graph, the paths from each node corresponding to the branch cluster undirected graph to each node corresponding to the main cluster undirected graph can be determined, and the shortest path among the paths is determined as the shortest path from the branch cluster undirected graph to the main cluster undirected graph.
[0049] Method (2): For each branch cluster undirected graph, the Dijkstra shortest path algorithm can be used to traverse the path from each node in the branch cluster undirected graph to the main cluster undirected graph, and the shortest path among the paths is determined as the shortest path from the branch cluster undirected graph to the main cluster undirected graph. The Dijkstra shortest path algorithm is a single-source shortest path algorithm. The Dijkstra algorithm uses a greedy strategy to gradually build a shortest path tree. The algorithm starts from the starting node and divides all nodes in the undirected graph into two parts: one part is the set of nodes for which the shortest path has been found (referred to as set A). Initially, there is only the starting node in set A; the other part is the set of nodes for which the shortest path has not yet been determined (referred to as set B). The algorithm continuously selects nodes from set B that are "distance from the starting node" and adds them to set A through an iterative process, and updates the shortest path from each node in set B to the starting node until set B is empty. The Dijkstra shortest path algorithm uses a greedy strategy and can efficiently find the shortest path from a node to other nodes. This makes the Dijkstra algorithm more efficient in processing large-scale graph structures such as pipeline network undirected graphs, far higher than the efficiency of manual verification. In addition, the Dijkstra algorithm can accurately calculate the shortest path, which is also the first application of this algorithm in this field.
[0050] Method (3): Divide the pipeline network undirected graph into four quadrants. If there are nodes in any branch cluster undirected graph and some nodes in the main cluster undirected graph in the same quadrant, only calculate the path from the node in the branch cluster undirected graph to the node in the corresponding quadrant of the main cluster undirected graph. Then, determine the shortest path among the paths as the shortest path from the branch cluster undirected graph to the main cluster undirected graph to reduce the amount of calculation.
[0051] Furthermore, pipeline network breakpoints may be determined based on the shortest paths.
[0052] Optionally, in the process of determining the shortest path from the branch cluster undirected graph to the main cluster undirected graph, the weight of the edge in the pipeline network undirected graph may be replaced with the length of the municipal road, so that the shortest path is also the shortest municipal road.
[0053] In the above embodiment, the shortest path from the branch cluster undirected graph to the main cluster undirected graph is determined, and then the pipeline network breakpoints are determined based on the shortest paths, thereby improving the accuracy of the pipeline network breakpoints.
[0054] In one embodiment, determining the pipeline network breakpoint based on each of the shortest paths includes: The shortest path that is smaller than a preset breakpoint threshold is determined as the pipeline network breakpoint.
[0055] Specifically, each shortest path can be compared with a preset breakpoint threshold, and then the shortest path less than the preset breakpoint threshold can be determined as the pipeline network breakpoint. It is easy to understand that the preset breakpoint threshold can be set according to the road conditions. For example, the preset breakpoint threshold can be 300 meters or 400 meters. Exemplarily, if the two pipe wells corresponding to the shortest path are on the same side of the same road, the preset breakpoint threshold can be set to 400 meters. Alternatively, if there are two pipe wells corresponding to the shortest paths on different roads near the intersection, the preset breakpoint threshold can be set to 300 meters. The specific setting of the preset breakpoint threshold can be obtained by field surveys using tools such as measuring wheels and rangefinders, and by measurement after drawing a drawing.
[0056] It is easy to understand that for the shortest path greater than or equal to the preset breakpoint threshold, it can be considered that the pipeline network corresponding to the branch cluster undirected graph does not need to be connected to the pipeline network corresponding to the main cluster undirected graph.
[0057] In the above embodiment, the shortest path smaller than the preset breakpoint threshold is determined as the pipeline network breakpoint, which can accurately identify the pipeline network breakpoint.
[0058] The automatic identification method of pipeline network breakpoints provided in the embodiment of the present application determines the pipeline network undirected graph based on the location information of multiple pipeline networks, and then determines the clustering conditions corresponding to all pipeline networks based on the pipeline network undirected graph. Further based on the clustering conditions, the pipeline network breakpoints are determined. The technical solution of the present invention does not require manual identification of pipeline network breakpoints, improves accuracy and identification efficiency, and reduces labor costs.
[0059] In addition, experiments have shown that the automatic identification method of pipeline network breakpoints provided in this application is 10 times more efficient and reduces costs by 40% compared to the prior art method of manually identifying pipeline network breakpoints.
[0060] The following is a description of an automatic identification device for pipeline network breakpoints provided in an embodiment of the present application. The automatic identification device for pipeline network breakpoints described below and the automatic identification method for pipeline network breakpoints described above can be referenced to each other.
[0061] Figure 5 Schematic diagram of the structure of the automatic identification device of pipeline network breakpoints provided in the embodiment of the present application. Figure 5 , an embodiment of the present application provides an automatic identification device 500 for pipeline network breakpoints, including the following undirected graph module 510, clustering module 520 and breakpoint module 530.
[0062] An undirected graph module 510, configured to determine an undirected graph of a pipeline network based on location information of a plurality of pipeline networks; A clustering module 520, configured to determine the clustering conditions corresponding to all the pipeline networks based on the pipeline network undirected graph; The breakpoint module 530 is used to determine the pipeline network breakpoint based on the clustering situation.
[0063] In one embodiment, the undirected graph module 510 is specifically used to: For each of the pipeline networks, a pipe well in the pipeline network is used as a node in a sub-undirected graph corresponding to the pipeline network; and a connection line between two pipe wells in the pipeline network is used as an edge in the sub-undirected graph; Based on the location information corresponding to all the sub-undirected graphs and all the pipe wells, the pipeline network undirected graph is determined.
[0064] In one embodiment, the undirected graph module 510 is further used to: Based on the corresponding position information of all the pipe wells, the sub-undirected graphs with the same pipe wells are connected to determine at least one cluster undirected graph; The pipeline network undirected graph is determined based on all cluster undirected graphs.
[0065] In one embodiment, the clustering situation includes a main cluster undirected graph and a branch cluster undirected graph, and the clustering module 520 is specifically used for: Based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the cluster undirected graph with the largest number of nodes is determined as a main cluster undirected graph, and the other cluster undirected graphs except the main cluster undirected graph are determined as branch cluster undirected graphs.
[0066] In one embodiment, the breakpoint module 530 is specifically used to: For each of the branch cluster undirected graphs, based on the position information of each node corresponding to the branch cluster undirected graph and the position information of each node corresponding to the main cluster undirected graph, determine the shortest path from the branch cluster undirected graph to the main cluster undirected graph; The pipeline network breakpoints are determined based on the shortest paths.
[0067] In one embodiment, the breakpoint module 530 is further configured to: The shortest path that is smaller than a preset breakpoint threshold is determined as the pipeline network breakpoint.
[0068] The automatic identification device of pipeline network breakpoints provided in the embodiment of the present application determines the pipeline network undirected graph based on the location information of multiple pipeline networks, and then determines the clustering conditions corresponding to all pipeline networks based on the pipeline network undirected graph. Further based on the clustering conditions, the pipeline network breakpoints are determined. The technical solution of the present invention does not require manual identification of pipeline network breakpoints, improves accuracy and identification efficiency, and reduces labor costs.
[0069] Figure 6 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 6 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call a computer program in the memory 630 to execute the steps of the automatic identification method of the pipeline network breakpoint, including the following steps.
[0070] Determine an undirected graph of a pipeline network based on location information of the plurality of pipeline networks; Based on the pipeline network undirected graph, determining the clustering conditions corresponding to all the pipeline networks; Based on the clustering situation, pipeline network breakpoints are determined.
[0071] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.
[0072] On the other hand, an embodiment of the present application also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the steps of the automatic identification method of pipeline network breakpoints provided in the above embodiments, including the following steps.
[0073] Determine an undirected graph of a pipeline network based on location information of the plurality of pipeline networks; Based on the pipeline network undirected graph, determining the clustering conditions corresponding to all the pipeline networks; Based on the clustering situation, pipeline network breakpoints are determined.
[0074] On the other hand, an embodiment of the present application further provides a processor-readable storage medium, wherein the processor-readable storage medium stores a computer program, and the computer program is used to enable the processor to execute the steps of the automatic identification method of pipeline network breakpoints provided in the above embodiments, including the following steps.
[0075] Determine an undirected graph of a pipeline network based on location information of a plurality of pipeline networks; Based on the pipeline network undirected graph, determining the clustering conditions corresponding to all the pipeline networks; Based on the clustering situation, pipeline network breakpoints are determined.
[0076] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.
[0077] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.
[0078] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.
Claims
1. A method for automatically identifying pipeline network breakpoints, characterized in that: include: Determine an undirected graph of a pipeline network based on location information of the plurality of pipeline networks; Based on the pipeline network undirected graph, determining the clustering conditions corresponding to all the pipeline networks; Based on the clustering situation, pipeline network breakpoints are determined.
2. The automatic identification method of pipeline network breakpoints according to claim 1 is characterized in that: The pipeline network includes two pipe wells, which are end points of the pipeline network; The step of determining the pipeline network undirected graph based on the location information of the plurality of pipeline networks comprises: For each of the pipeline networks, a pipe well in the pipeline network is used as a node in a sub-undirected graph corresponding to the pipeline network; and a connection line between two pipe wells in the pipeline network is used as an edge in the sub-undirected graph; Based on the location information corresponding to all the sub-undirected graphs and all the pipe wells, the pipeline network undirected graph is determined.
3. The automatic identification method of pipeline network breakpoints according to claim 2 is characterized in that: The step of determining the pipeline network undirected graph based on the location information corresponding to all the sub-undirected graphs and all the pipe wells includes: Based on the location information corresponding to all the pipe wells, the sub-undirected graphs with the same pipe wells are connected to determine at least one cluster undirected graph; The pipeline network undirected graph is determined based on all cluster undirected graphs.
4. The automatic identification method of pipeline network breakpoints according to claim 3 is characterized in that: The clustering situation includes a main cluster undirected graph and a branch cluster undirected graph, and the determining of the clustering situations corresponding to all the pipeline networks based on the pipeline network undirected graph includes: Based on the number of nodes corresponding to each cluster undirected graph in the pipeline network undirected graph, the cluster undirected graph with the largest number of nodes is determined as a main cluster undirected graph, and the other cluster undirected graphs except the main cluster undirected graph are determined as branch cluster undirected graphs.
5. The method for automatically identifying pipeline network breakpoints according to claim 4, characterized in that: The step of determining pipeline network breakpoints based on the clustering situation includes: For each of the branch cluster undirected graphs, based on the position information of each node corresponding to the branch cluster undirected graph and the position information of each node corresponding to the main cluster undirected graph, determine the shortest path from the branch cluster undirected graph to the main cluster undirected graph; The pipeline network breakpoints are determined based on the shortest paths.
6. The automatic identification method of pipeline network breakpoints according to claim 5 is characterized in that: The determining the pipeline network breakpoint based on each of the shortest paths comprises: The shortest path that is smaller than a preset breakpoint threshold is determined as the pipeline network breakpoint.
7. An automatic identification device for pipeline network breakpoints, characterized in that: include: An undirected graph module, used for determining an undirected graph of a pipeline network based on location information of a plurality of pipeline networks; A clustering module, used for determining the clustering conditions corresponding to all the pipeline networks based on the pipeline network undirected graph; The breakpoint module is used to determine the pipeline network breakpoint based on the clustering situation.
8. An electronic device comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the computer program, the steps of the method for automatically identifying pipeline network breakpoints according to any one of claims 1 to 6 are implemented.
9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for automatically identifying pipeline network breakpoints as described in any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for automatically identifying pipeline network breakpoints as described in any one of claims 1 to 6 are implemented.