Underground pipeline fault positioning method and device applied to urban underground pipe network

Abstract

Embodiments of the present disclosure disclose a method and device for underground pipeline fault positioning applied to urban underground pipe network. A specific embodiment of the method comprises: obtaining a multi-source underground pipeline operation dataset from a city data platform; simulating operation of a pre-constructed urban underground pipe network model according to the multi-source underground pipeline operation dataset to obtain a target pipe network model; segmenting pipeline structures of simulated underground pipelines in a simulated underground pipeline group included in the target pipe network model to generate a segmented simulated pipeline group set; dividing a buffer zone of the simulated underground pipelines in the simulated underground pipeline group included in the target pipe network model to generate a pipeline buffer area set; and performing pipeline fault detection on the target pipe network model according to the segmented simulated pipeline group set and the pipeline buffer area set to generate pipeline fault positioning information. The embodiment can accurately position faults of underground pipelines.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the fields of computer technology and underground pipeline fault detection, specifically to underground pipeline fault location methods and apparatus applied to urban underground pipe networks. Background Technology

[0002] Underground pipelines are mostly concealed underground projects, laid for power, water, and gas transmission. Due to the constraints of the outgoing corridors, multiple lines often intersect and overlap, posing certain safety hazards. For example, inconsistent workmanship or quality at cable joints, or overheating due to constant load operation, lead to frequent failures. Furthermore, because underground cables have limited monitoring methods and lack effective monitoring and early warning mechanisms, inspection workloads are heavy, and fault location is difficult.

[0003] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not form prior art known to those skilled in the art. Summary of the Invention

[0004] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0005] Some embodiments of this disclosure propose a method and apparatus for locating underground pipeline faults in urban underground pipe networks, in order to solve the technical problems mentioned in the background section above.

[0006] In a first aspect, some embodiments of this disclosure provide a method for locating underground pipeline faults in urban underground pipe networks. The method includes: acquiring a multi-source underground pipeline operation dataset from an urban data platform, wherein the multi-source underground pipeline operation dataset is the actual operation data of the urban underground pipe network; simulating a pre-constructed urban underground pipe network model based on the multi-source underground pipeline operation dataset to obtain a target pipe network model, wherein the urban underground pipe network model is constructed based on the spatial distribution of the urban underground pipe network, and the target pipe network model is used to synchronously simulate the operation of the urban underground pipe network, the target pipe network model including simulated underground pipeline groups; segmenting the simulated underground pipelines in the simulated underground pipeline groups included in the target pipe network model to generate a set of segmented simulated pipeline groups; dividing the simulated underground pipelines in the simulated underground pipeline groups included in the target pipe network model into buffer zones to generate a set of pipeline buffer areas; and performing pipeline fault detection on the target pipe network model based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas to generate pipeline fault location information.

[0007] Secondly, some embodiments of this disclosure provide an underground pipeline fault location device applied to urban underground pipe networks. The device includes: an acquisition unit configured to acquire a multi-source underground pipeline operation dataset from an urban data platform, wherein the multi-source underground pipeline operation dataset is the actual operation data of the urban underground pipe network; and a simulation operation unit configured to simulate a pre-constructed urban underground pipe network model based on the aforementioned multi-source underground pipeline operation dataset to obtain a target pipe network model, wherein the urban underground pipe network model is constructed based on the spatial distribution of the urban underground pipe network, and the target pipe network model is used to synchronously simulate the urban underground pipe network. The system operates as follows: the target pipeline network model includes simulated underground pipeline groups; a pipeline structure segmentation unit is configured to segment the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model to generate a set of segmented simulated pipeline groups; a buffer zone division unit is configured to divide the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model into buffer zones to generate a set of pipeline buffer areas; and a fault detection and location unit is configured to perform pipeline fault detection on the target pipeline network model based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas to generate pipeline fault location information.

[0008] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0009] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0010] The above-described embodiments of this disclosure have the following beneficial effects: The underground pipeline fault location method applied to urban underground pipe networks according to some embodiments of this disclosure can accurately locate faults in underground pipelines. Specifically, the lack of effective monitoring methods and early warning mechanisms is due to the fact that underground pipe networks are mostly concealed underground projects, laid underground for power transmission, water transmission, gas transmission, etc. Due to the limitations of the outgoing corridor, multiple lines intersect and overlap, posing certain safety hazards. For example, inconsistent workmanship or quality at cable joints, or severe overheating due to constant load operation, lead to frequent faults. Furthermore, because the monitoring methods for underground cables are relatively limited, and there is a lack of effective monitoring methods and early warning mechanisms, the inspection pressure is high, and fault location is difficult. Based on this, the underground pipeline fault location method applied to urban underground pipe networks according to some embodiments of this disclosure obtains a multi-source underground pipeline operation dataset from an urban data platform. This multi-source underground pipeline operation dataset represents the actual operation data of the urban underground pipe network. Here, by obtaining multi-source underground pipeline operation data, it can be used to coordinate fault location by combining various different underground pipelines. For example, power transmission lines, water supply lines, and gas pipelines. Then, based on the aforementioned multi-source underground pipeline operation dataset, a pre-constructed urban underground pipeline network model is simulated to obtain a target pipeline network model. This urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network. By constructing the target pipeline network model, the operation of the urban underground pipeline network can be simulated synchronously. The target pipeline network model includes simulated underground pipeline groups. This facilitates fault location using the target pipeline network model. Next, the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model are segmented to generate a set of segmented simulated pipeline groups. This segmentation allows for precise fault location. Then, buffer zones are created for the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model to generate a set of pipeline buffer areas. Here, dividing the buffer zones helps determine the impact range of different pipelines when a fault occurs. Finally, based on the aforementioned set of segmented simulated pipeline groups and the aforementioned set of pipeline buffer zones, pipeline fault detection is performed on the target pipeline network model to generate pipeline fault location information. This allows for precise location of faults in underground pipelines. Attached Figure Description

[0011] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0012] Figure 1 This is a flowchart of some embodiments of the underground pipeline fault location method applied to urban underground pipe networks according to the present disclosure;

[0013] Figure 2 This is a schematic diagram of a segmented simulated pipeline;

[0014] Figure 3 This is a schematic diagram of the pipeline buffer area;

[0015] Figure 4 This is a schematic diagram of the structure of some embodiments of the underground pipeline fault location device applied to urban underground pipe networks according to the present disclosure;

[0016] Figure 5 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0017] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0018] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0019] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0020] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0021] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0022] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0023] Figure 1 A flowchart 100 is shown, illustrating some embodiments of a method for locating underground pipeline faults in urban underground pipe networks according to this disclosure. The method for locating underground pipeline faults in urban underground pipe networks includes the following steps:

[0024] Step 101: Obtain multi-source underground pipeline operation dataset from the city data platform.

[0025] In some embodiments, the implementing entity (e.g., a computing device) of the underground pipeline fault location method applied to urban underground pipe networks can acquire multi-source underground pipeline operation datasets from an urban data platform via wired or wireless means. These multi-source underground pipeline operation datasets are the actual operational data of the urban underground pipe network. The urban data platform may include, but is not limited to, at least one of the following: an electricity pipeline platform, a water supply pipeline platform, a gas pipeline platform, or a communication pipeline platform. Thus, operational data from underground pipelines of different sources and types can be acquired as multi-source underground pipeline operation data. Each multi-source underground pipeline operation data corresponds to one underground pipeline.

[0026] It should be noted that the aforementioned computing devices can be either hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is software, it can be installed on the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0027] Step 102: Based on the multi-source underground pipeline operation dataset, simulate the pre-built urban underground pipeline network model to obtain the target pipeline network model.

[0028] In some embodiments, the aforementioned execution entity can simulate the operation of a pre-constructed urban underground pipeline network model based on the aforementioned multi-source underground pipeline operation dataset to obtain a target pipeline network model. The urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network, and the target pipeline network model can be used to synchronously simulate the operation of the urban underground pipeline network. The target pipeline network model may include simulated underground pipeline groups. Here, the simulation operation can be performed by filling the corresponding simulated underground pipelines in the urban underground pipeline network model with multi-source underground pipeline operation data according to the resource transmission direction of the underground pipelines (e.g., the direction of power flow) to synchronously simulate the operation of the urban underground pipeline network.

[0029] In practice, multi-source underground pipeline operation datasets can be used to simulate the flow paths of fluids (such as tap water), electricity, or other resources using shortest path algorithms (e.g., Dixtro's algorithm) to simulate the operation of underground pipeline networks in urban underground pipeline network models.

[0030] As an example, simulations can also be performed using simulation software. For instance, simulation software may include, but is not limited to, at least one of the following: COMSOL multiphysics simulation software, ANSYS simulation software, MATLAB simulation and modeling tools, WaterGEMS (water engineering modeling system), SYSTEM SAT (Simulation and Analysis Tool) gas / heating pipeline network simulation software, etc.

[0031] Step 103: Perform pipeline structure segmentation on the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model to generate a set of segmented simulated pipeline groups.

[0032] In some embodiments, the executing entity may segment the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model to generate a set of segmented simulated pipeline groups. This segmentation can be performed using pipeline nodes included in the target pipeline network model. Pipeline nodes can represent the locations of pipe wells along the pipeline path.

[0033] In some optional implementations of certain embodiments, the execution entity segments the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model to generate a set of segmented simulated pipeline groups, which may include the following steps:

[0034] The first step is to obtain the pipeline structure dataset of the target pipeline network model. This can be achieved by retrieving the pipeline structure data corresponding to each simulated underground pipeline in the target pipeline network model from the aforementioned urban data platform. The pipeline structure data may include the path coordinate sequence of the simulated underground pipelines and the pipeline connection identifier group sequence. Each pipeline connection identifier group can correspond to one simulated underground pipeline, representing all simulated underground pipelines that are connected to that simulated underground pipeline.

[0035] The second step involves determining the pipe inflection point coordinates of each simulated underground pipeline in the aforementioned simulated underground pipeline group, based on the aforementioned pipeline network structure dataset, thus obtaining a set of pipe inflection point coordinate groups. The pipe inflection point coordinates of the simulated underground pipelines can be determined through the following steps: For each path coordinate, firstly, using the coordinates of the two adjacent paths, the curvature value at the location of that path coordinate is determined through the second derivative. Then, the path coordinates corresponding to curvature values ​​greater than a preset curvature threshold are determined as the pipe inflection point coordinates. Each simulated underground pipeline can correspond to one set of pipe inflection point coordinates.

[0036] Alternatively, pre-trained random forest or support vector machine models can be used to identify inflection points in simulated underground pipelines, generating sets of pipeline inflection point coordinates. The model's training labels can include manually labeled inflection points and extracted features. Extracted features can include curvature values, direction vectors, and the angle between adjacent line segments.

[0037] In practice, considering the nonlinear characteristics of underground pipelines, nonlinear algorithms are used to enhance the data to more accurately reflect the actual shape of the pipelines. These include, but are not limited to, machine learning-based algorithms (such as neural networks and support vector machines), which can handle complex nonlinear relationships and extract features such as bending and undulation of the pipeline from the raw data. This improves the efficiency of pipeline fault location.

[0038] The third step involves interpolating the inflection point coordinates of each inflection point in the aforementioned set of pipeline inflection point coordinate sets according to a preset inflection point coordinate spacing, thereby obtaining the target inflection point coordinate set. First, it can be determined whether the distance between adjacent inflection point coordinates is greater than twice the aforementioned inflection point coordinate spacing. If it is greater than twice the inflection point coordinate spacing, then interpolation is performed towards the midpoint between adjacent inflection point coordinates. This process yields the target inflection point coordinate set.

[0039] The fourth step involves segmenting each simulated underground pipeline in the aforementioned set of target inflection point coordinates into segments, based on the target inflection point coordinates set. Specifically, the midpoint coordinates between any two target inflection points can be determined, and the segment between two adjacent midpoint coordinates can then be defined as a segmented simulated pipeline. Each segmented simulated pipeline corresponds to the target inflection point coordinates between two midpoint coordinates.

[0040] As an example, participate Figure 2 The diagram shown is a segmented simulation of a cable pipeline. Figure 2 The center point (the black dot on the dashed line) of each dashed line can represent the coordinates of the target inflection point. Each dashed line can represent a division of the simulated pipeline (such as a cable). Therefore, a segmented simulated pipeline is the pipeline between two (or three) dashed lines.

[0041] Step 104: Divide the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model into buffer zones to generate a pipeline buffer zone set.

[0042] In some embodiments, the executing entity may divide the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model into buffer zones to generate a pipeline buffer area set. Specifically, the area where simulated underground pipelines with interconnections are located can be defined as a pipeline buffer area. Here, the interconnection can be between simulated underground pipelines of the same type and corresponding to the same pipeline connection identifier.

[0043] In some optional implementations of certain embodiments, the execution entity performs buffer partitioning on the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model to generate a pipeline buffer region set, which may include the following steps:

[0044] The first step is to extract the pipeline nodes of the simulated underground pipelines from the above-mentioned simulated underground pipeline group, thus obtaining a set of pipeline node groups. Here, a pipeline node is a connection point of underground pipelines of the same type. The connection point can represent the location of a pipeline connection or the location of a pipe well. Specifically, the pipeline nodes of each simulated underground pipeline can be extracted from the target pipeline network model to obtain the set of pipeline node groups.

[0045] The second step is to merge the aforementioned set of target inflection point coordinates with the aforementioned set of pipeline node sets to obtain a set of target pipeline node sets. Specifically, both the target inflection point coordinates and the pipeline nodes can be considered as target pipeline nodes to obtain the target pipeline node set.

[0046] The third step is to obtain the pipeline parameter information corresponding to the simulated underground pipelines in the simulated underground pipeline group, thus obtaining a pipeline parameter information set. This pipeline parameter information may include: a sequence of pipeline structural parameters. These pipeline structural parameters correspond to path coordinates, representing the pipeline specifications at the corresponding path coordinate location. Pipeline specifications may include pipeline dimensions, pipeline material identification, and pipeline age identification, etc.

[0047] The fourth step is to determine the intersection points of the simulated underground pipelines in the above-mentioned simulated underground pipeline group, and obtain the coordinate set of the pipeline intersection points. The coordinates of the pipeline intersection points correspond to the intersection points of underground pipelines of different types. Here, the coordinates of the intersection of two simulated underground pipelines can be determined as the pipeline intersection point.

[0048] In practice, gas pipelines, water supply pipelines, and sewage pipelines are strictly prohibited from sharing the same utility tunnel during design and construction, therefore, there are no intersection points. Thus, the pipeline intersection point can be the intersection point of cable pipelines and communication pipelines. Furthermore, even if no intersection point exists, if a fault in a gas pipeline, water supply pipeline, or sewage pipeline affects a large area, it can still impact cable pipelines and communication pipelines.

[0049] The fifth step involves performing a pipeline risk association analysis on the simulated underground pipelines in the simulated underground pipeline group based on the aforementioned pipeline parameter information set and pipeline intersection coordinate set, to generate a pipeline cross-influence information set. Each pipeline cross-influence information set corresponds to at least two simulated underground pipelines. Here, the following association steps are performed for each simulated underground pipeline: First, other simulated underground pipelines corresponding to the coordinates of each pipeline intersection on the simulated underground pipeline are identified as associated underground pipelines, resulting in a set of associated underground pipelines. Then, the association risk score value between the simulated underground pipeline and each associated underground pipeline is determined, resulting in a set of association risk score values. For associated underground pipelines with association risk score values ​​greater than a preset score threshold, the association steps are repeated to identify other associated underground pipelines with which the associated underground pipeline has a risk association. Therefore, the simulated underground pipelines and associated underground pipelines with association risk score values ​​greater than the preset score threshold can be marked as cross-influence pipelines. Finally, each group of marked cross-impact pipelines and its corresponding associated risk score can be identified as pipeline cross-impact information.

[0050] Specifically, a risk score can be generated by simulating underground pipelines and their associated pipeline parameter information. Specifically, the score corresponding to the pipe size and age of the pipe material can be selected from a pre-defined score table. For example, the score table can include score ranges for different pipe materials, pipe sizes, and pipe ages. For instance, a record in the score table could be: polyethylene sheathed cable, service life: [15-20 years], pipe size: [50 mm], with a corresponding score of 12 points. Here, a smaller score indicates a lower hidden risk in the pipeline.

[0051] Step 6: Based on the aforementioned pipeline intersection impact information set, divide the target pipeline nodes in the aforementioned target pipeline node group set into pipeline buffer zones to generate a pipeline buffer zone set. Here, a pipeline buffer zone is a pipeline risk range defined by the target pipeline node as a risk point. The pipeline buffer zone includes a pipeline association subnet composed of multiple related simulated underground pipelines and / or segmented simulated pipelines. Specifically, the pipeline buffer zone corresponding to the target pipeline node can be determined according to the area corresponding to each intersecting pipeline marked in each pipeline intersection impact information, thus obtaining the pipeline buffer zone set. Furthermore, the pipeline buffer zones corresponding to various target pipeline nodes on the same simulated underground pipeline can be the same. Specifically, a pipeline buffer zone can characterize the potential risk area of ​​a simulated underground pipeline.

[0052] In practice, firstly, it's important to consider the often interconnected effects at intersection points. For example, an unexpected fault (such as a leakage) between different pipeline types (communication lines and power supply lines) can easily affect both types of pipelines at the intersection point. Similarly, for pipelines of the same type, a cable fault at one point can easily lead to voltage anomalies in other related cables, or even prevent normal power supply. Therefore, pipeline intersection points are determined from both the perspectives of similar and dissimilar pipeline types. Next, to further delineate pipeline buffer zones, pipeline risk correlation analysis can be used to associate simulated underground pipelines with associated risks. Based on this, the areas corresponding to associated simulated underground pipelines can be merged into pipeline buffer zones according to pipeline cross-influence information. This allows for precise delineation of pipeline buffer zones for each simulated underground pipeline, facilitating accurate fault location in subsequent operations.

[0053] As an example, see Figure 3 The diagram shows a pipeline buffer zone. Figure 3 Solid lines can represent multiple simulated underground pipelines or segmented simulated pipelines that have interconnected influences, with the intersection points being the target pipeline nodes. Thus, each solid line forms a pipeline interconnection subnet, and the area corresponding to each solid line is the pipeline buffer zone. Here, the area corresponding to each simulated underground pipeline can be a pre-defined fixed range. Figure 3 The dashed line can represent another pipeline-related subnet, that is, another pipeline buffer zone. Although the pipelines in the two pipeline buffer zones have intersection points, they are divided into two different pipeline buffer zones because their mutual influence is small.

[0054] Step 105: Based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas, perform pipeline fault detection on the target pipeline network model to generate pipeline fault location information.

[0055] In some embodiments, the execution entity may perform pipeline fault detection on the target pipeline network model based on the segmented simulated pipeline group set and the pipeline buffer area set to generate pipeline fault location information.

[0056] In some optional implementations of certain embodiments, the execution entity performs pipeline fault detection on the target pipeline network model based on the segmented simulated pipeline group set and the pipeline buffer region set to generate pipeline fault location information, which may include the following steps:

[0057] The first step involves fault detection on the target pipeline network model to generate abnormal pipeline groups and fault identifiers. This includes detecting operational data from multiple underground pipelines within the target network model; if the detected operational data exceeds a preset data threshold, a pipeline is identified as abnormal. Then, the simulated underground pipelines containing the operational data exceeding the preset threshold are identified. Finally, the data anomaly type of the abnormal pipeline is determined as a fault identifier, and each simulated underground pipeline is identified as an abnormal pipeline group.

[0058] As an example, if the voltage of the power supply cable exceeds a preset voltage threshold, the indicator representing the voltage abnormality can be identified as a fault indicator.

[0059] The second step is to select the segmented simulated pipelines corresponding to the above-mentioned abnormal pipeline groups from the above-mentioned segmented simulated pipeline group set, and obtain the abnormal segmented simulated pipeline group set.

[0060] The third step is to select pipeline buffer zones from the above pipeline buffer zones that correspond to the abnormal segmented simulated pipelines in the above abnormal segmented simulated pipeline group set, and obtain the abnormal pipeline buffer group set.

[0061] The fourth step involves batch merging the aforementioned abnormal pipeline buffer groups according to the set of abnormal segmented simulated pipeline groups, to generate a first fault buffer and a second fault buffer. The first fault buffer is a region of the same pipeline type as the simulated pipeline segment, and the second fault buffer is a region of a different pipeline type. Batch merging can involve combining the abnormal pipeline buffers corresponding to the same pipeline type of abnormal segmented simulated pipelines into the first fault buffer. Then, the abnormal pipeline buffers corresponding to different pipeline types in the aforementioned abnormal pipeline buffer group set are combined into the first fault buffer. In practice, the first fault buffer can be used to characterize the affected area of ​​a fault of the same pipeline type. The second fault buffer can be used to characterize the area where abnormal segmented simulated pipelines of other pipeline types with related influences are located.

[0062] The fifth step is to determine the above-mentioned abnormal pipeline group, the above-mentioned fault identifier, the above-mentioned abnormal segmented simulated pipeline group set, the first fault buffer zone and the second fault buffer zone as pipeline fault location information.

[0063] In practice, simulating pipeline segments by locating anomalies can accurately represent the location of pipeline faults, thus achieving precise fault localization. Furthermore, by using flow analysis algorithms to simulate fluid or electrical flow in underground pipe networks and assessing the impact range and potential risks of intersection areas during flow, a first and second fault buffer zone can be defined. This provides a more accurate assessment of the impact range for pipeline fault handling, thereby improving fault handling efficiency.

[0064] Optionally, the above-mentioned urban underground pipe network model can be constructed through the following steps:

[0065] The first step is to obtain a multi-source underground pipeline construction dataset. Each multi-source underground pipeline construction dataset may include: pipeline parameters, a 3D underground pipeline coordinate sequence, and underground pipeline node groups. The underground pipeline node group may include underground pipeline nodes representing connection points between underground pipelines and other pipelines, and underground pipeline nodes representing the coordinates of pipeline atriums. Here, the 3D underground pipeline coordinates can be the coordinates on the centerline of the pipeline.

[0066] The second step involves analyzing the 3D underground pipeline coordinate sequence included in the multi-source underground pipeline construction data set to generate a pipeline orientation dataset. Specifically, the direction vector of each 3D underground pipeline coordinate location can be determined using the aforementioned machine learning algorithm, serving as the pipeline orientation data.

[0067] The third step involves establishing an urban underground pipeline network model within a pre-defined urban coordinate system. This model is based on the pipeline route dataset and the multi-source underground pipeline construction data from the aforementioned multi-source underground pipeline construction dataset, including pipeline parameters, 3D underground pipeline coordinate sequences, and underground pipeline node groups. This urban underground pipeline network model can be created using 3D modeling software or modeling scripts. Furthermore, during the modeling process, pipelines are generated centered on the 3D underground pipeline coordinates, following the order of the 3D underground pipeline coordinates in the 3D underground pipeline coordinate sequence and using the constraint of filling pipeline parameters with direction vectors. Finally, the positions of the underground pipeline nodes are marked, resulting in the urban underground pipeline network model.

[0068] As an example, 3D modeling software may include, but is not limited to, at least one of the following: AutoCAD (Automatic Computer Aided Design) platform, 3ds Max modeling platform, or Revit building information model, etc.

[0069] In practice, the established urban underground pipeline network model can be visualized to intuitively demonstrate the three-dimensional structural distribution of underground power distribution lines and other pipelines. This provides decision support for the scientific allocation and utilization of urban underground space resources.

[0070] Here, considering that actual pipelines can easily damage existing pipelines during construction, leading to pipeline failures, it's crucial to further avoid such problems. Therefore, based on the constructed urban underground pipeline network model, the construction route can be located in advance to determine if any conflicts exist. This can significantly reduce the likelihood of pipeline failures.

[0071] Optionally, the aforementioned implementing entity may also perform the following steps:

[0072] The first step involves receiving the current construction simulation pipeline entry information from the construction design terminal, and adding the current construction simulation pipeline, as included in the current pipeline entry information, to the target pipeline network model to obtain the current pipeline network model. The construction design terminal can be a terminal used for designing construction routes. The current construction simulation pipeline entry information can be the information of the current construction simulation pipeline uploaded after the construction route design. Secondly, the current construction simulation pipeline can be added to the corresponding positions in the target pipeline network model according to the path coordinates and pipeline specification parameters of the construction design to obtain the current pipeline network model.

[0073] The second step involves performing a conflict analysis on the simulated pipelines in the current pipeline network model to generate conflict analysis results. These results may include conflict identifiers and conflicting pipeline information. The conflict identifiers indicate whether the simulated pipelines in the current construction phase have spatial conflicts with simulated underground pipelines, and the conflicting pipeline information includes the simulated underground pipelines involved in the conflict and their corresponding spatial locations.

[0074] In practice, spatial location conflict can indicate that the current construction simulation pipeline route design conflicts with the routes of other underground pipelines that have already been laid.

[0075] The third step involves adjusting the current simulated construction pipeline based on the conflict identifiers identified in the conflict analysis results, resulting in an adjusted construction pipeline. The conflict analysis results and the adjusted construction pipeline are then returned to the construction design terminal. This adjustment can be achieved using a shortest path algorithm, with the aforementioned spatial location area acting as an obstacle region.

[0076] In some optional implementations of certain embodiments, the execution entity performs conflict analysis on the current construction simulation pipeline in the current pipeline network model to generate conflict analysis results, which may include the following steps:

[0077] The first step is to establish a 3D construction-occupied area corresponding to the currently simulated construction pipeline in the existing pipeline network model, and to establish pipeline simulation tunnels corresponding to each simulated underground pipeline, thus obtaining the construction inspection pipeline network model. The information entered for the currently simulated construction pipeline may also include the pipeline dimensions and the construction passage dimensions. Here, the 3D construction-occupied area can be marked in the current pipeline network model according to the construction passage dimensions of the currently simulated construction pipeline. Similarly, pipeline simulation tunnels corresponding to other simulated underground pipelines can be marked according to the passage dimensions of those pipelines, thereby obtaining the construction inspection pipeline network model.

[0078] The second step is to determine whether there is a spatial conflict between the construction-occupied 3D area and the simulated tunnels of each pipeline in the aforementioned construction and inspection network model. Specifically, this involves determining whether the construction-occupied 3D area and the simulated tunnels of each pipeline share the same coordinates. If they do, and they are not pipeline nodes, then a spatial conflict exists. Furthermore, the relationship between the construction-occupied 3D area and the simulated tunnels of the pipelines with spatial conflicts is marked as a spatial conflict relationship.

[0079] The third step is to generate a pipeline conflict identifier to represent the pipeline conflict in response to the spatial location conflict between the construction-occupied three-dimensional area and the pipeline simulation tunnel.

[0080] The fourth step involves determining whether the currently simulated construction pipeline in the aforementioned construction and inspection pipeline network model has a positional conflict with other simulated underground pipelines. This can be achieved by comparing the range of the currently simulated construction pipeline with the ranges of other simulated underground pipelines in the current pipeline network model to see if they share the same coordinates. Simultaneously, it's determined whether the shared coordinates represent pipeline nodes. If they exist, and the shared coordinates are not pipeline nodes, it indicates a spatial positional conflict between the currently simulated construction pipeline and other simulated underground pipelines. This relationship is then marked as a positional conflict. This allows for efficient and direct determination of whether pipeline conflicts exist.

[0081] The fifth step is to generate a pipeline conflict identifier to represent the location conflict between the current construction simulation pipeline and the simulation underground pipeline in response to the location conflict.

[0082] The sixth step involves identifying the aforementioned pipeline conflict markers and the corresponding simulated underground pipelines and spatial location regions as conflict analysis results. Here, segmented simulated pipelines corresponding to the same coordinates can be identified. Then, the spatial region of each segmented simulated pipeline is defined as the spatial location region. The spatial region of each segmented simulated pipeline can be the area it occupies in three-dimensional space.

[0083] In practice, the relative position and spatial relationship between planned underground (power distribution) pipelines and other pipelines can be identified through three-dimensional pipeline intersection positioning analysis. This can be used to optimize pipeline construction design schemes and avoid pipeline failures caused by construction conflicts.

[0084] The above-described embodiments of this disclosure have the following beneficial effects: The underground pipeline fault location method applied to urban underground pipe networks according to some embodiments of this disclosure can accurately locate faults in underground pipelines. Specifically, the lack of effective monitoring methods and early warning mechanisms is due to the fact that underground pipe networks are mostly concealed underground projects, laid underground for power transmission, water transmission, gas transmission, etc. Due to the limitations of the outgoing corridor, multiple lines intersect and overlap, posing certain safety hazards. For example, inconsistent workmanship or quality at cable joints, or severe overheating due to constant load operation, lead to frequent faults. Furthermore, because the monitoring methods for underground cables are relatively limited, and there is a lack of effective monitoring methods and early warning mechanisms, the inspection pressure is high, and fault location is difficult. Based on this, the underground pipeline fault location method applied to urban underground pipe networks according to some embodiments of this disclosure obtains a multi-source underground pipeline operation dataset from an urban data platform. This multi-source underground pipeline operation dataset represents the actual operation data of the urban underground pipe network. Here, by obtaining multi-source underground pipeline operation data, it can be used to coordinate fault location by combining various different underground pipelines. For example, power transmission lines, water supply lines, and gas pipelines. Then, based on the aforementioned multi-source underground pipeline operation dataset, a pre-constructed urban underground pipeline network model is simulated to obtain a target pipeline network model. This urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network. By constructing the target pipeline network model, the operation of the urban underground pipeline network can be simulated synchronously. The target pipeline network model includes simulated underground pipeline groups. This facilitates fault location using the target pipeline network model. Next, the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model are segmented to generate a set of segmented simulated pipeline groups. This segmentation allows for precise fault location. Then, buffer zones are created for the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model to generate a set of pipeline buffer areas. Here, dividing the buffer zones helps determine the impact range of different pipelines when a fault occurs. Finally, based on the aforementioned set of segmented simulated pipeline groups and the aforementioned set of pipeline buffer zones, pipeline fault detection is performed on the target pipeline network model to generate pipeline fault location information. This allows for precise location of faults in underground pipelines.

[0085] Further reference Figure 4As an implementation of the methods shown in the above figures, this disclosure provides some embodiments for locating underground pipeline faults in urban underground pipe networks. These device embodiments are similar to... Figure 1 Corresponding to the method embodiments shown, the underground pipeline fault location device applied to urban underground pipe networks can be specifically applied to various electronic devices.

[0086] like Figure 4 As shown, an underground pipeline fault location device 400 applied to urban underground pipe networks in some embodiments includes: an acquisition unit 401, a simulation operation unit 402, a pipeline structure segmentation unit 403, a buffer zone division unit 404, and a fault detection and location unit 405. The acquisition unit 401 is configured to acquire a multi-source underground pipeline operation dataset from an urban data platform, wherein the multi-source underground pipeline operation dataset is the actual operation data of the urban underground pipe network; the simulation operation unit 402 is configured to simulate the operation of a pre-constructed urban underground pipe network model based on the aforementioned multi-source underground pipeline operation dataset to obtain a target pipe network model, wherein the urban underground pipe network model is constructed based on the spatial distribution of the urban underground pipe network, and the target pipe network model is used to synchronously simulate the operation of the urban underground pipe network, including simulated underground pipeline groups; Line structure segmentation unit 403 is configured to segment the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model to generate a set of segmented simulated pipeline groups; buffer zone division unit 404 is configured to divide the simulated underground pipelines in the simulated underground pipeline group included in the target pipeline network model into buffer zones to generate a set of pipeline buffer areas; fault detection and location unit 405 is configured to perform pipeline fault detection on the target pipeline network model based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas to generate pipeline fault location information.

[0087] It is understandable that the units described in the underground pipeline fault location device 400 applied to urban underground pipe networks are similar to those in the reference system. Figure 1 The steps described in the method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method are also applicable to the underground pipeline fault location device 400 and its constituent units applied to urban underground pipe networks, and will not be repeated here.

[0088] The following is for reference. Figure 5 It shows a schematic diagram of the structure of an electronic device (such as a computing device) suitable for implementing some embodiments of the present disclosure. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of this disclosure. Figure 5As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The memory may include a non-volatile storage medium and internal memory. The non-volatile storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause the processor to perform any of the methods described above. The processor provides computational and control capabilities to support the operation of the entire computer device. The internal memory provides an environment for the execution of the computer program in the non-volatile storage medium; when executed by the processor, the computer program causes the processor to perform any of the methods described above. The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0089] It should be understood that the processor can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, a general-purpose processor can be a microprocessor or any conventional processor.

[0090] In one embodiment, the processor is configured to run a computer program stored in a memory to perform the following steps: obtaining a multi-source underground pipeline operation dataset from an urban data platform, wherein the multi-source underground pipeline operation dataset is the actual operation data of the urban underground pipeline network; simulating a pre-constructed urban underground pipeline network model based on the multi-source underground pipeline operation dataset to obtain a target pipeline network model, wherein the urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network, and the target pipeline network model is used to synchronously simulate the operation of the urban underground pipeline network, the target pipeline network model including simulated underground pipeline groups; segmenting the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model to generate a set of segmented simulated pipeline groups; dividing the simulated underground pipelines in the simulated underground pipeline groups included in the target pipeline network model into buffer zones to generate a set of pipeline buffer areas; and performing pipeline fault detection on the target pipeline network model based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas to generate pipeline fault location information.

[0091] This disclosure also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, and the method implemented when the program instructions are executed can be referred to various embodiments of the methods described above in this disclosure.

[0092] The aforementioned computer-readable storage medium may be an internal storage unit of the computer device described in the foregoing embodiments, such as the hard disk or memory of the computer device. Alternatively, the aforementioned computer-readable storage medium may be an external storage device of the computer device, such as a plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the computer device.

[0093] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0094] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for locating underground pipeline faults in urban underground pipe networks, characterized in that, include: The multi-source underground pipeline operation dataset is obtained from the city data platform. The multi-source underground pipeline operation dataset is the actual operation data of the city's underground pipeline network. Based on the multi-source underground pipeline operation dataset, the pre-constructed urban underground pipeline network model is simulated to obtain the target pipeline network model. The urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network. The target pipeline network model is used to synchronously simulate the operation of the urban underground pipeline network. The target pipeline network model includes simulated underground pipeline groups. Obtain the pipeline structure dataset of the target pipeline model; Based on the pipeline network structure dataset, determine the pipe inflection point coordinates of each simulated underground pipeline in the simulated underground pipeline group to obtain a set of pipe inflection point coordinate groups. According to the preset inflection point coordinate spacing, the inflection point coordinates of each inflection point coordinate group in the pipeline inflection point coordinate group set are interpolated to obtain the target inflection point coordinate group set. Based on the target inflection point coordinates in the target inflection point coordinate set, each simulated underground pipeline in the simulated underground pipeline group is segmented to obtain a segmented simulated pipeline group set. Extract the pipeline nodes of the simulated underground pipelines in the simulated underground pipeline group to obtain a set of pipeline node groups, where the pipeline node is the connection point of the underground pipelines of the same type. The target inflection point coordinate set is fused with the pipeline node set to obtain the target pipeline node set. Obtain the pipeline parameter information corresponding to the simulated underground pipelines in the simulated underground pipeline group to obtain the pipeline parameter information set; The intersection points of the simulated underground pipelines in the simulated underground pipeline group are determined to obtain the coordinate set of the pipeline intersection points, wherein the coordinates of the pipeline intersection points are the intersection points of underground pipelines corresponding to different pipeline types; Based on the pipeline parameter information set and the pipeline intersection point coordinate set, a pipeline risk correlation analysis is performed on the simulated underground pipelines in the simulated underground pipeline group to generate a pipeline intersection impact information set, wherein each pipeline intersection impact information corresponds to at least two simulated underground pipelines; Based on the pipeline intersection impact information set, the target pipeline nodes in the target pipeline node group set are divided into pipeline buffer areas to generate a pipeline buffer area set. The pipeline buffer area is a pipeline risk range divided with the target pipeline node as the risk point. The pipeline buffer area includes a pipeline association subnet composed of multiple related simulated underground pipelines and / or segmented simulated pipelines. Based on the set of segmented simulated pipeline groups and the set of pipeline buffer areas, pipeline fault detection is performed on the target pipeline network model to generate pipeline fault location information.

2. The method according to claim 1, characterized in that, The method further includes: In response to receiving the current construction simulation pipeline entry information from the construction design terminal, the current construction simulation pipeline included in the current construction simulation pipeline entry information is added to the target pipeline network model to obtain the current pipeline network model; In the current pipeline network model, a conflict analysis is performed on the current construction simulation pipeline to generate conflict analysis results. The conflict analysis results include conflict identifiers and conflict pipeline information. The conflict identifiers indicate whether the current construction simulation pipeline has a spatial conflict with the simulated underground pipeline. The conflict pipeline information includes the simulated underground pipeline with the conflict and the corresponding spatial location area. In response to the conflict analysis results indicating a spatial conflict, the current construction simulation pipeline is adjusted to obtain the adjusted construction pipeline, and the conflict analysis results and the adjusted construction pipeline are returned to the construction design terminal.

3. The method according to claim 1, characterized in that, The step of performing pipeline fault detection on the target pipeline network model based on the segmented simulated pipeline group set and the pipeline buffer area set to generate pipeline fault location information includes: Fault detection is performed on the target pipeline model to generate abnormal pipeline groups and fault identifiers; Select the segmented simulated pipelines corresponding to the abnormal pipeline groups from the segmented simulated pipeline group set to obtain the abnormal segmented simulated pipeline group set; From the pipeline buffer area set, select the pipeline buffer area corresponding to the abnormal segment simulated pipeline in the abnormal segment simulated pipeline group set to obtain the abnormal pipeline buffer group set; According to the set of abnormal segmented simulated pipeline groups, the set of abnormal pipeline buffer groups is merged in batches to generate a first fault buffer and a second fault buffer. The first fault buffer is a region of the same pipeline type as the pipeline segmented simulated pipeline, and the second fault buffer is a region of a different pipeline type than the pipeline segmented simulated pipeline. The abnormal pipeline group, the fault identifier, the abnormal segmented simulated pipeline group set, the first fault buffer, and the second fault buffer are identified as pipeline fault location information.

4. The method according to claim 2, characterized in that, The step of performing conflict analysis on the current construction simulation pipeline in the current pipeline network model to generate conflict analysis results includes: In the current pipeline network model, a three-dimensional area for construction occupation corresponding to the current construction simulation pipeline is established, and pipeline simulation tunnels corresponding to each simulated underground pipeline are established to obtain a construction inspection pipeline network model. In the construction inspection pipeline network model, determine whether there is a spatial conflict between the three-dimensional area occupied by construction and the simulated tunnels of each pipeline; In response to the spatial location conflict between the construction-occupied 3D area and the pipeline simulation tunnel, a pipeline conflict identifier is generated to represent the pipeline conflict. In the construction inspection pipeline network model, determine whether the current construction simulation pipeline has a positional conflict relationship with other simulated underground pipelines; In response to the locational conflict between the current simulated construction pipeline and the simulated underground pipeline, a pipeline conflict identifier is generated to represent the pipeline conflict. The pipeline conflict markers and pipe conflict markers are identified as conflict markers, and the conflict markers and the corresponding simulated underground pipelines and spatial location areas are identified as conflict analysis results.

5. The method according to claim 1, characterized in that, The urban underground pipe network model is constructed through the following steps: Obtain a multi-source underground pipeline construction dataset, in which each multi-source underground pipeline construction dataset includes: pipeline parameters, three-dimensional underground pipeline coordinate sequence, and underground pipeline node group; The pipeline orientation analysis is performed on the three-dimensional underground pipeline coordinate sequence included in the multi-source underground pipeline construction data in the multi-source underground pipeline construction data set to generate a pipeline orientation data set. In the preset urban coordinate system, an urban underground pipeline network model is established based on the pipeline route dataset and the pipeline parameters, three-dimensional underground pipeline coordinate sequence and underground pipeline node group included in the multi-source underground pipeline construction data in the multi-source underground pipeline construction dataset.

6. A fault location device for underground pipelines in urban underground pipe networks, comprising: The acquisition unit is configured to acquire a multi-source underground pipeline operation dataset from the city data platform, wherein the multi-source underground pipeline operation dataset is the actual operation data of the city's underground pipeline network; The simulation operation unit is configured to simulate the operation of a pre-built urban underground pipeline network model based on the multi-source underground pipeline operation dataset to obtain a target pipeline network model. The urban underground pipeline network model is constructed based on the spatial distribution of the urban underground pipeline network, and the target pipeline network model is used to synchronously simulate the operation of the urban underground pipeline network. The target pipeline network model includes a simulated underground pipeline group. The pipeline structure segmentation unit is configured to acquire the pipeline structure dataset of the target pipeline model; determine the pipeline inflection point coordinates of each simulated underground pipeline in the simulated underground pipeline group based on the pipeline structure dataset, thereby obtaining a set of pipeline inflection point coordinate groups; perform inflection point coordinate interpolation on each inflection point coordinate group in the set of pipeline inflection point coordinates according to a preset inflection point coordinate interval, thereby obtaining a target inflection point coordinate group set; and segment each simulated underground pipeline in the simulated underground pipeline group based on the target inflection point coordinates in the target inflection point coordinate group set, thereby obtaining a set of segmented simulated pipeline groups. The buffer partitioning unit is configured to extract pipeline nodes of simulated underground pipelines in the simulated underground pipeline group to obtain a set of pipeline node groups, wherein pipeline nodes are connection points of underground pipelines of the same type; merge the target inflection point coordinate set with the pipeline node group set to obtain a target pipeline node group set; obtain pipeline parameter information corresponding to the simulated underground pipelines in the simulated underground pipeline group to obtain a set of pipeline parameter information; determine the pipeline intersection points of simulated underground pipelines in the simulated underground pipeline group to obtain a set of pipeline intersection point coordinates, wherein the pipeline intersection point coordinates are intersection points of underground pipelines of different types; root Based on the pipeline parameter information set and the pipeline intersection point coordinate set, a pipeline risk correlation analysis is performed on the simulated underground pipelines in the simulated underground pipeline group to generate a pipeline intersection impact information set, wherein each pipeline intersection impact information corresponds to at least two simulated underground pipelines; based on the pipeline intersection impact information set, pipeline buffer zones are divided for the target pipeline nodes in the target pipeline node group set to generate a pipeline buffer zone set, wherein the pipeline buffer zone is a pipeline risk range divided with the target pipeline node as the risk point, and the pipeline buffer zone includes a pipeline association subnet composed of multiple related simulated underground pipelines and / or segmented simulated pipelines; The fault detection and location unit is configured to perform pipeline fault detection on the target pipeline network model based on the segmented simulated pipeline group set and the pipeline buffer area set, so as to generate pipeline fault location information.

7. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-5.

8. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-5.

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