A method and system for troubleshooting high-risk points of electrical faults in underground pipe corridors

Abstract

The present invention discloses a method and system for troubleshooting high-risk electrical fault points in underground pipe corridors, which relate to the field of fire prevention technology. The method collects data from multiple sensors, combines it with historical equipment operation and maintenance data, generates an electrical topology network based on cable paths and equipment connection relationships, constructs a three-dimensional model of the pipe corridor, and performs fire prediction simulations. This method effectively predicts and locates fire occurrence points, saving equipment maintenance costs, and replacing some manual inspections, reducing the workload of ineffective troubleshooting.

Description

Technical Field

[0001] The present invention relates to the technical field of fire prevention, and in particular to a method and system for checking high-risk points of electrical faults in underground pipe corridors. Background Art

[0002] Underground utility corridors, the lifeline of urban infrastructure, centrally house power, communications, water supply, and drainage pipelines. These systems significantly address the "road zipper" problem associated with traditional direct-buried pipelines, improving urban resilience and land utilization. These systems have become widely used in China. However, underground utility corridor fires are often caused by electrical faults, the effects of which spread exponentially. Repairing underground utility corridors is costly, disrupts public services, and creates the risk of collapse, resulting in severe social impacts. Consequently, a method for predicting fires caused by electrical faults in underground utility corridors is urgently needed. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for troubleshooting high-risk points of electrical faults in underground pipe corridors, so as to improve the above-mentioned technical problems.

[0004] In order to achieve the above-mentioned object of the invention, the embodiment of the present invention provides the following technical solutions:

[0005] A method for troubleshooting high-risk points of electrical faults in underground pipe corridors, comprising:

[0006] Real-time acquisition of operating environment data for the underground integrated pipe corridor; the operating environment data includes modeling environment parameters, historical sensor data, real-time operating data, historical equipment operation and maintenance management data, and pipe corridor structural parameters; modeling environment parameters include spatial coordinate information of the underground integrated pipe corridor and comprehensive sensor data;

[0007] Construct a three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters;

[0008] Based on historical equipment operation and maintenance management data and historical sensor data, the electrical evolution law of the underground integrated pipeline corridor is analyzed and the electrical spatiotemporal evolution function is constructed;

[0009] Based on the electrical spatiotemporal evolution function, the modeling environment parameters and real-time operation data are input into the three-dimensional model of the pipeline corridor and simulated to obtain the simulation results;

[0010] Based on the simulation results, high-risk points for electrical failures are identified; based on the principle of proximity, maintenance personnel are dispatched to inspect and repair high-risk points for electrical failures.

[0011] Furthermore, sensor data includes temperature, current, humidity, and wind speed;

[0012] Real-time operation data includes electrical parameters and equipment status parameters; equipment status parameters include equipment start / stop status and vibration data;

[0013] Historical equipment operation and maintenance management data includes historical equipment management data and historical real-time operation data; historical equipment management data includes historical fault records, maintenance logs and historical weather data;

[0014] The structural parameters of the underground utility corridor include the design drawing data, equipment ID, equipment spatial coordinate data and equipment parameters of the underground utility corridor; the design drawing data includes spatial structure parameters, electrical equipment size data, cable paths and equipment connection relationships; the equipment parameters include cable model, insulation material characteristics, rated current and voltage, etc.

[0015] Furthermore, the real-time acquisition of the operating environment data of the underground integrated pipe gallery includes:

[0016] Deploy different types of sensors in underground integrated pipeline corridors to build an IoT sensor network;

[0017] Collect pipeline corridor structural parameters, real-time operating parameters, historical equipment operation and maintenance management data, and historical sensor raw data;

[0018] The original modeling environmental parameters of the underground integrated pipeline corridor are collected in real time through the IoT sensor network;

[0019] The original modeling environment parameters are denoised using wavelet transform. By decomposing the signal into wavelet basis functions of different scales, the high-frequency noise components are separated and removed to obtain the initial modeling environment parameters.

[0020] The initial modeling environment parameters and historical sensor raw data are supplemented by generative adversarial networks to obtain modeling environment parameters and historical sensor data.

[0021] Furthermore, the construction of the three-dimensional model of the pipeline corridor includes:

[0022] Based on the pipeline corridor structural parameters, construct the original pipeline corridor 3D model;

[0023] Based on the design drawing data and equipment ID, set nodes, edges, and edge weights, connect the spatial coordinate data of the original pipeline corridor 3D model, and build an electrical topology network;

[0024] The electrical topology network and the original pipeline corridor 3D model are fused through spatial matching and attribute merging operations to obtain the initial 3D pipeline corridor model.

[0025] Calculate feature diameter; calculate mesh size based on feature diameter;

[0026] The grid size is applied to the initial three-dimensional model of the pipeline corridor to obtain the three-dimensional model of the pipeline corridor.

[0027] Furthermore, the construction of the electrical spatiotemporal evolution function includes:

[0028] Construct a full-scale model of the power compartment in the blocked underground integrated pipeline corridor and conduct a fire scenario simulation to obtain corresponding fire simulation results; the fire simulation results include flameout time, flame spread image, and heat release simulation rate curve;

[0029] Fuse and analyze fire simulation results, historical equipment operation and maintenance management data, and historical sensor data to obtain the fire fusion original feature matrix;

[0030] Integrate fire simulation results, historical equipment operation and maintenance management data, and historical real-time operation data to obtain fire fusion status data;

[0031] Constructing a time-varying function of electrical insulation materials; calculating a time-varying correction term based on the time-varying function of electrical insulation materials;

[0032] Based on the time-varying correction term, the LSTM-Transformer hybrid network is used to analyze the original feature matrix of fire fusion and construct the electrical spatiotemporal evolution function.

[0033] Furthermore, the process of obtaining the simulation results includes:

[0034] Input modeling environment parameters and real-time operation data into the three-dimensional model of the pipeline corridor;

[0035] Based on the electrical spatiotemporal evolution function, real-time scenario simulation is performed through the three-dimensional model of the pipeline corridor. Monte Carlo simulation is used to simulate the fire spread process in different scenarios, and the corresponding fire source occurrence point and extinguishing time are recorded;

[0036] The fire spread process under different scenarios is recorded and the corresponding fire spread heat map is drawn; the simulation results include the fire source point, extinguishing time and fire spread heat map.

[0037] Furthermore, the dispatching of maintenance personnel to inspect and repair high-risk points of electrical faults includes:

[0038] Feedback the spatial coordinates of the fire source point through the three-dimensional model of the pipeline corridor;

[0039] Based on each spatial coordinate, calculate the distance between each fire source and each fire door;

[0040] Determine the danger level of each fire source based on the extinguishing time, distance and fire spread heat map;

[0041] Based on the danger level, high-risk points of electrical failure are determined; according to the principle of proximity, different maintenance personnel are dispatched to inspect and repair high-risk points of electrical failure.

[0042] Furthermore, feedback processing is also included, including:

[0043] Maintenance results and post-maintenance electrical data are uploaded, packaged, and organized in real time, and fed back to the three-dimensional model of the pipeline corridor and the LSTM-Transformer hybrid network. The hyperparameters of the LSTM-Transformer hybrid network are updated in real time, and the structural parameters of the three-dimensional model of the pipeline corridor are updated.

[0044] A system for troubleshooting high-risk points of electrical faults in underground pipe corridors, comprising:

[0045] An operating environment data acquisition module is used to obtain the operating environment data of the underground integrated pipe corridor in real time; the operating environment data includes modeling environment parameters, historical sensor data, real-time operation data, historical equipment operation and maintenance management data, and pipe corridor structural parameters; the modeling environment parameters include the spatial coordinate information of the underground integrated pipe corridor and comprehensive sensor data;

[0046] The three-dimensional model construction module of the pipeline corridor is used to construct the three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters;

[0047] The electrical spatiotemporal evolution function construction module is used to analyze the electrical evolution laws of underground utility corridors and construct electrical spatiotemporal evolution functions based on historical equipment operation and maintenance management data and historical sensor data;

[0048] The three-dimensional model simulation module of the utility corridor inputs modeling environment parameters and real-time operation data into the three-dimensional model of the utility corridor based on the electrical time-space evolution function and performs simulation to obtain simulation results;

[0049] The module for determining high-risk points for electrical faults and planning the path for elimination is used to determine high-risk points for electrical faults based on simulation results; based on the principle of proximity, maintenance personnel are dispatched to inspect and repair high-risk points for electrical faults.

[0050] The beneficial effects of the present invention are:

[0051] The present invention discloses a method and system for troubleshooting high-risk electrical fault points in underground pipe corridors, which relate to the field of fire prevention technology. The method collects data from multiple sensors, combines it with historical equipment operation and maintenance data, generates an electrical topology network based on cable paths and equipment connection relationships, constructs a three-dimensional model of the pipe corridor, and performs fire prediction simulations. This method effectively predicts and locates fire occurrence points, saving equipment maintenance costs, and replacing some manual inspections, reducing the workload of ineffective troubleshooting. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without making any creative efforts.

[0053] Figure 1 A flow chart of a method in an embodiment of the present invention;

[0054] Figure 2 2 is a system structure diagram in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 This embodiment provides a method for troubleshooting high-risk electrical fault points in an underground utility corridor, including:

[0057] S1. Acquire the operating environment data of the underground integrated pipeline corridor in real time; the operating environment data includes modeling environment parameters, historical sensor data, real-time operation data, historical equipment operation and maintenance management data, and pipeline corridor structure parameters.

[0058] The modeling environment parameters include the spatial coordinate information of the underground integrated pipeline corridor and the sensor comprehensive data; the sensor comprehensive data includes sensor location data, sensor data and acquisition timestamp; the sensor data includes temperature, current, humidity, wind speed and carbon dioxide concentration.

[0059] Real-time operating data includes electrical parameters (power, power factor, and frequency) and equipment status parameters. Equipment status parameters include the equipment's start and stop status and vibration data.

[0060] Historical equipment operation and maintenance management data includes historical equipment management data and historical real-time operation data. This data includes historical fault records, maintenance logs, and historical weather data. Historical fault records (fault time, type, location, repair measures, etc.) and maintenance logs (repair time, personnel, and details, etc.) are extracted from the equipment operation and maintenance management system. Historical weather data (temperature, humidity, rainfall, wind speed, etc.) is obtained from the meteorological department.

[0061] Utility corridor structural parameters include the design drawing data, equipment ID, equipment spatial coordinate data, and equipment parameters for the underground utility corridor. The design drawing data includes spatial structural parameters, electrical equipment dimensions, cable routing, and equipment connection relationships. Equipment parameters include cable model, insulation material properties, and rated current and voltage.

[0062] In this embodiment, the cables in the underground integrated pipeline corridor include YC cables and RVV cables.

[0063] Said S1 comprises:

[0064] S1-1. Deploy various types of sensors in the underground utility corridor to build an IoT sensor network. Temperature sensors should be arranged in a circular pattern at 5-meter intervals around cable joints and distribution cabinets. Temperature sensors should be placed at intervals of 12 meters along the corridor's longitudinal direction on the top, bottom, and sidewalls of the cable tray. Current sensors should be placed at key points in the distribution circuit; these include but are not limited to the inlet and outlet terminals of the ring main unit, intermediate cable joints, and power supply branches with a load factor exceeding 80%. Humidity sensors should be installed in areas prone to water accumulation, ventilation openings, and at the bottom of cable shafts. Wind speed sensors should be placed at the intersection of ventilation openings (1.5 meters from the main corridor entrance / exit), at the boundaries of fire compartments (on both sides of each partition door), and in cable areas. A carbon dioxide concentration sensor should be placed at each end and in the middle of the cable tray.

[0065] S1-2, collect pipeline corridor structural parameters, real-time operating parameters, historical equipment operation and maintenance management data, and historical sensor raw data;

[0066] S1-3. Collect the original modeling environmental parameters of the underground integrated pipeline corridor in real time through the Internet of Things sensor network.

[0067] S1-4. Use wavelet transform to denoise the original modeling environment parameters. By decomposing the signal into wavelet basis functions of different scales, the high-frequency noise components are separated and removed to obtain the initial modeling environment parameters.

[0068] S1-5. The initial modeling environment parameters and historical sensor raw data are supplemented by a generative adversarial network to obtain the modeling environment parameters and historical sensor data.

[0069] S2. Construct a three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters.

[0070] The S2 includes:

[0071] S2-1. Construct the original three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters.

[0072] The S2-1 includes:

[0073] S2-1-1. Input the design drawing data, equipment ID, and equipment parameters of the tunnel structure parameters into the BIM software to construct a 3D tunnel structure model. BIM software can be Autodesk Revit or Bentley MicroStation.

[0074] S2-1-2. Import the three-dimensional structural model of the pipeline corridor into the GIS software, annotate it based on the sensor position data and spatial coordinate information in the modeling environment parameters, and construct the original three-dimensional model of the pipeline corridor, namely the BIM-GIS pipeline corridor model.

[0075] S2-2. Based on the design drawing data and equipment ID, set the nodes, edges, and edge weights, connect the spatial coordinate data of the original pipeline corridor 3D model, and build the electrical topology network.

[0076] The S2-2 includes:

[0077] S2-2-1. Extract the cable paths and equipment connection relationships in the design drawing data, and use the equipment and cable connection relationships as nodes respectively. and the edge , using cable impedance as edge weight to construct the electrical graph structure The equipment is the electrical device of the underground integrated pipeline corridor, such as cable connectors, distribution cabinets, etc.

[0078] S2-2-2. Input the device spatial coordinate data, device ID and spatial coordinate data into the electrical diagram structure, analyze the connection relationship between the devices, and build the electrical topology network.

[0079] S2-3. The electrical topology network and the original 3D pipe corridor model are integrated through spatial matching and attribute merging operations to obtain the initial 3D pipe corridor model. Spatial matching uses an R-tree index to achieve precise alignment of device coordinates. The attribute merging operation merges the BIM-GIS attributes of the 3D pipe corridor model with the topological attributes of the electrical topology network one by one; for example, coordinate data in the BIM-GIS is integrated with node coordinate data in the electrical topology network.

[0080] S2-4. Calculate the characteristic diameter; calculate the grid size based on the characteristic diameter. The corresponding formula is:

[0081] ;

[0082] ;

[0083] in, represents the characteristic diameter, Indicates the fire heat release rate in kW. 、 、 They represent the ambient air concentration, specific heat capacity of air at constant pressure and ambient air temperature, respectively, and their units are kg / m 3 , kJ / (kg·k), K, Indicates the acceleration due to gravity in m / s 2 . represents the grid size, Represents the parameter that controls the grid resolution, and its value range is [4,16].

[0084] S2-5. Apply the grid size to the initial three-dimensional model of the pipeline corridor to obtain the three-dimensional model of the pipeline corridor.

[0085] S3. Based on historical equipment operation and maintenance management data and historical sensor data, analyze the electrical evolution law of the underground integrated pipeline corridor and construct the electrical spatiotemporal evolution function.

[0086] The S3 includes:

[0087] S3-1. Construct a full-scale model of the power compartment in the blocked underground integrated pipeline corridor and conduct a fire scenario simulation to obtain corresponding fire simulation results; the fire simulation results include flameout time, flame spread image and heat release simulation rate curve.

[0088] S3-2. Fusion and analysis of fire simulation results, historical equipment operation and maintenance management data, and historical sensor data to obtain the fire fusion original feature matrix.

[0089] Fire simulation results, historical equipment operation and maintenance management data, and historical sensor data are integrated to obtain fire fusion state data. Data mining and feature extraction are performed on the fire fusion state data to extract features related to temperature and current changes during fires, thereby obtaining the fire fusion original feature matrix.

[0090] S3-3. Construct a time-varying function of the electrical insulation material; calculate the time-varying correction term based on the time-varying function of the electrical insulation material.

[0091] S3-4. Based on the time-varying correction term, the LSTM-Transformer hybrid network is used to analyze the original feature matrix of fire fusion and construct the electrical spatiotemporal evolution function.

[0092] The LSTM-Transformer hybrid network is used to extract the electrical evolution law of temperature and current in the pipe gallery during the fire. Therefore, the formula corresponding to the electrical spatiotemporal evolution function is:

[0093] ;

[0094] ;

[0095] ;

[0096] ;

[0097] ;

[0098] in, represents the integral function, represents the output of the LSTM neural network, 、 Represent the Transformer network function and its output respectively, Indicates the current time The fire fusion original feature matrix, Indicates the current time The first temperature prediction value, 、 represent the uncertainty coupling coefficient and Joule heating coefficient respectively, Indicates time The square of the current inside, Indicates time The resistance value inside represents the concatenation function, Indicates the current time The time-varying correction term of represents the initial time-varying correction term, represents a natural constant, 、 represent the uncertainty attenuation coefficient and thermal diffusion coefficient, respectively. represents the second temperature prediction value, 、 Respectively indicate time Device temperature, ambient temperature (temperature measured by the sensor), represents the initial temperature, represents the Laplace operator of the temperature field, Indicates the quality of pipe gallery equipment. represents the specific heat capacity, represents the thermal dissipation coefficient, represents the fusion weight, represents the residual noise term.

[0099] S4. Based on the electrical spatiotemporal evolution function, the modeling environment parameters and real-time operation data are input into the three-dimensional model of the pipeline corridor and simulated to obtain the simulation results.

[0100] The S4 includes:

[0101] S4-1. Input the sensor data, timestamps, and real-time operation data in the modeling environment parameters into the three-dimensional model of the pipeline corridor.

[0102] S4-2. Based on the electrical spatiotemporal evolution function, real-time scenario simulation is performed through the three-dimensional model of the pipeline corridor. Monte Carlo simulation is used to simulate the fire spread process under different scenarios, and the corresponding fire source occurrence point and extinguishing time are recorded.

[0103] S4-3. Record the fire spread process in different scenarios and draw the corresponding fire spread heat map.

[0104] The temperature field data, smoke concentration field, and structural damage status (0 for intact, 0.5 for partially damaged, and 1 for completely damaged) during each fire spread process were divided into 10-s intervals, and the divided data were integrated to obtain the corresponding fire spread data.

[0105] Calculate the comprehensive thermal value corresponding to the fire spread data. The comprehensive thermal value is calculated using the existing method. For example, the temperature weight, smoke weight, and damage weight are multiplied by the corresponding data and added together to obtain the corresponding value, which is the comprehensive thermal value. Setting the temperature weight, smoke weight, and damage weight needs to follow the setting conditions. For example, in the early stage of a fire or half a minute before the fire occurs, the temperature weight can be set to 0.8. This is because in the early stage of a fire, the temperature rises faster, there is only a little smoke and some equipment is on fire, and the degree of damage is not high; in the middle stage of a fire, the ratio of the temperature weight to the smoke weight can be close to 1:1, and the set value is larger than the damage weight, because in the middle stage of development, the temperature may tend to be stable, with little fluctuation, resulting in a large amount of smoke, and burning or damaging equipment; in the late stage of a fire, the fire subsides and smoke is diffuse. At this time, the smoke weight is the largest, followed by the damage weight and the temperature weight.

[0106] Based on the comprehensive thermal value, the fire spread process is rendered in three dimensions to obtain the corresponding rendering image, that is, the fire spread thermal map.

[0107] The simulation results include the fire source point, extinguishing time and fire spread thermal map.

[0108] S5. Based on the simulation results, identify high-risk points for electrical faults; based on the principle of proximity, dispatch maintenance personnel to inspect and repair high-risk points for electrical faults.

[0109] S5-1. Feedback the spatial coordinates corresponding to the fire source point through the three-dimensional model of the pipeline corridor.

[0110] S5-2. Based on the spatial coordinates, calculate the distance between each fire source and each fire door.

[0111] If a fire occurs in the middle of each tunnel, this location can be considered a high-risk point because it is far away from the fire door openings on both sides, making fire rescue difficult and the fire cannot be controlled in the fastest time. Therefore, the distance factor needs to be taken into consideration when determining the high-risk point of electrical faults.

[0112] S5-3. Determine the danger level of each fire source based on the extinguishing time, distance, and fire spread heat map.

[0113] A color threshold is set, and thermal areas larger than the color threshold are extracted using an edge extraction algorithm. The thermal area of the thermal area is calculated. The ratio of the thermal area to the area of the fire spread thermogram is calculated and used as the thermal hazard level.

[0114] Thermal hazard level based on each fire source , Extinguishing time and distance , calculate the danger level .

[0115] The formula corresponding to the hazard level is:

[0116] ;

[0117] in, 、 Indicates the risk factor.

[0118] S5-4. Based on the hazard level, determine the high-risk points of electrical faults; according to the principle of proximity, dispatch different maintenance personnel to inspect and repair the high-risk points of electrical faults.

[0119] Set the first, second, and third danger thresholds. If the danger level reaches the first danger threshold, the fire source is considered a high-risk electrical fault point. If the danger level reaches the second danger threshold, the fire source is considered a medium-risk electrical fault point. If the danger level reaches the third danger threshold, the fire source is considered a non-electrical fault point.

[0120] During maintenance, the system obtains the location of the maintenance station and the maintenance type of the maintenance personnel. It calculates the distance between the maintenance station and the tunnel access, and assigns the maintenance personnel with electrical faults at the nearest maintenance station to the access point based on the distance. A path planning algorithm is then used to determine the maintenance route for each maintenance personnel based on the high-risk electrical fault locations.

[0121] Path planning algorithms can include ant colony optimization, particle swarm optimization, and dynamic programming (DP). For example, the ant colony optimization algorithm uses each tunnel maintenance entrance as the initial location of the ant colony. Each initial location contains several ants, and high-risk electrical fault points are considered nodes. The distance and pheromone profile of each ant to the next node are calculated. Based on the pheromone profile, each ant's route is selected until all nodes have been selected. Each ant's path serves as the inspection route for maintenance personnel. Based on the maintenance route, each maintenance personnel inspects the high-risk points.

[0122] In addition, dangerous points in electrical faults can be regarded as nodes, and the same method as the path planning method for high-risk points of electrical faults can be used to plan the inspection path for idle maintenance personnel.

[0123] In addition, step S5 also includes feedback processing. The feedback processing is:

[0124] Maintenance results and post-repair electrical data are uploaded, packaged, and fed back into the 3D tunnel model for updating. This data is also fed back into the LSTM-Transformer hybrid network, updating its hyperparameters in real time to better reflect the real-world situation. This improves the network's ability to accurately capture the tunnel's electrical spatiotemporal evolution, facilitating subsequent identification of high-risk electrical fault points.

[0125] The maintenance results include whether the equipment is working properly, the degree of equipment aging, whether the equipment has been replaced, whether the electrical components have been replaced, and the ID or location information of equipment that is not considered a high-risk point for electrical failure.

[0126] like Figure 2 As shown, a system for troubleshooting high-risk points of electrical faults in underground pipe corridors includes:

[0127] An operating environment data acquisition module is used to obtain the operating environment data of the underground integrated pipe corridor in real time; the operating environment data includes modeling environment parameters, historical sensor data, real-time operation data, historical equipment operation and maintenance management data, and pipe corridor structural parameters; the modeling environment parameters include the spatial coordinate information of the underground integrated pipe corridor and comprehensive sensor data;

[0128] The three-dimensional model construction module of the pipeline corridor is used to construct the three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters;

[0129] The electrical spatiotemporal evolution function construction module is used to analyze the electrical evolution laws of underground utility corridors and construct electrical spatiotemporal evolution functions based on historical equipment operation and maintenance management data and historical sensor data;

[0130] The three-dimensional model simulation module of the utility corridor inputs modeling environment parameters and real-time operation data into the three-dimensional model of the utility corridor based on the electrical time-space evolution function and performs simulation to obtain simulation results;

[0131] The module for determining high-risk points for electrical faults and planning the path for elimination is used to determine high-risk points for electrical faults based on simulation results; based on the principle of proximity, maintenance personnel are dispatched to inspect and repair high-risk points for electrical faults.

[0132] The system also includes a real-time feedback module for uploading and packaging maintenance results and post-repair electrical data in real time, and feeding them back to the three-dimensional model of the corridor and the LSTM-Transformer hybrid network, updating the structure of the three-dimensional model of the corridor (such as the replaced device name and ID) and adjusting the hyperparameters of the LSTM-Transformer hybrid network.

[0133] In summary, the present invention discloses a method and system for troubleshooting high-risk electrical fault points in underground utility corridors, which relate to the field of fire prevention technology. This system collects data from multiple sensors, combines it with historical equipment operation and maintenance data, generates an electrical topology network based on cable paths and equipment connection relationships, constructs a three-dimensional model of the utility corridor, and performs fire prediction simulations. This effectively predicts and locates fire points, saving equipment maintenance costs, and replacing some manual inspections, reducing the workload of ineffective troubleshooting.

[0134] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for troubleshooting high-risk points of electrical faults in underground pipe corridors, characterized in that: include: Obtain the operating environment data of the underground integrated pipeline corridor in real time; The operating environment data includes modeling environment parameters, historical sensor data, real-time operation data, historical equipment operation and maintenance management data, and pipe gallery structure parameters; the modeling environment parameters include spatial coordinate information and sensor comprehensive data of the underground integrated pipe gallery; the historical equipment operation and maintenance management data includes historical equipment management data and historical real-time operation data; Construct a three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters; Based on historical equipment operation and maintenance management data and historical sensor data, the electrical evolution law of the underground integrated pipeline corridor is analyzed and the electrical spatiotemporal evolution function is constructed; Based on the electrical spatiotemporal evolution function, the modeling environment parameters and real-time operation data are input into the three-dimensional model of the pipeline corridor and simulated to obtain the simulation results; Based on the simulation results, identify high-risk points for electrical faults; Based on the principle of proximity, dispatch maintenance personnel to inspect and repair high-risk points for electrical faults; The constructing of the electrical spatiotemporal evolution function includes: Construct a full-scale model of the power compartment in the blocked underground integrated pipeline corridor and conduct a fire scenario simulation to obtain corresponding fire simulation results; the fire simulation results include flameout time, flame spread image, and heat release simulation rate curve; Fuse and analyze fire simulation results, historical sensor data, and historical equipment operation and maintenance management data to obtain the fire fusion original feature matrix; Integrate fire simulation results, historical equipment operation and maintenance management data, and historical real-time operation data to obtain fire fusion status data; Constructing a time-varying function of electrical insulation materials; calculating a time-varying correction term based on the time-varying function of electrical insulation materials; Based on the time-varying correction term, the LSTM-Transformer hybrid network is used to analyze the original fire fusion feature matrix and construct the electrical spatiotemporal evolution function. The corresponding formula is: ； ； ； ； ； in, represents the integral function, represents the output of the LSTM neural network, 、 Represent the Transformer network function and its output respectively, Indicates the current time The fire fusion original feature matrix, Indicates the current time The first temperature prediction value, 、 represent the uncertainty coupling coefficient and Joule heating coefficient respectively, Indicates time The square of the current inside, Indicates time The resistance value inside represents the concatenation function, Indicates the current time The time-varying correction term of represents the initial time-varying correction term, represents a natural constant, 、 represent the uncertainty attenuation coefficient and thermal diffusion coefficient, respectively. represents the second temperature prediction value, 、 Respectively indicate time Device temperature, ambient temperature (temperature measured by the sensor), represents the initial temperature, represents the Laplace operator of the temperature field, Indicates the quality of pipe gallery equipment. represents the specific heat capacity, represents the thermal dissipation coefficient, represents the fusion weight, represents the residual noise term.

2. A method for troubleshooting high-risk points of electrical faults in underground pipe corridors according to claim 1, characterized in that: Sensor data includes temperature, current, humidity, and wind speed; Real-time operation data includes electrical parameters and equipment status parameters; equipment status parameters include equipment start / stop status and vibration data; Historical equipment management data includes historical fault records, maintenance logs, and historical weather data; The structural parameters of the underground utility corridor include the design drawing data, equipment ID, equipment spatial coordinate data and equipment parameters of the underground utility corridor; the design drawing data includes spatial structure parameters, electrical equipment size data, cable paths and equipment connection relationships; the equipment parameters include cable model, insulation material characteristics, and rated current and voltage.

3. A method for checking high-risk points of electrical faults in underground pipe corridors according to claim 1, characterized in that: The real-time acquisition of the operating environment data of the underground integrated pipe gallery includes: Deploy different types of sensors in underground integrated pipeline corridors to build an IoT sensor network; Collect pipeline corridor structural parameters, real-time operating parameters, historical equipment operation and maintenance management data, and historical sensor raw data; The original modeling environmental parameters of the underground integrated pipeline corridor are collected in real time through the IoT sensor network; The original modeling environment parameters are denoised using wavelet transform. By decomposing the signal into wavelet basis functions of different scales, the high-frequency noise components are separated and removed to obtain the initial modeling environment parameters. The initial modeling environment parameters and historical sensor raw data are supplemented by generative adversarial networks to obtain modeling environment parameters and historical sensor data.

4. A method for troubleshooting high-risk electrical fault points in an underground pipe gallery according to claim 2, characterized in that: The constructing of the three-dimensional model of the pipe gallery includes: Based on the pipeline corridor structural parameters, construct the original pipeline corridor 3D model; Based on the design drawing data and equipment ID, set nodes, edges, and edge weights, connect the spatial coordinate data of the original pipeline corridor 3D model, and build an electrical topology network; The electrical topology network and the original pipeline corridor 3D model are fused through spatial matching and attribute merging operations to obtain the initial 3D pipeline corridor model. Calculate feature diameter; calculate mesh size based on feature diameter; The grid size is applied to the initial three-dimensional model of the pipeline corridor to obtain the three-dimensional model of the pipeline corridor.

5. A method for troubleshooting high-risk points of electrical faults in underground pipe corridors according to claim 2, characterized in that: The process of obtaining the simulation results includes: Input modeling environment parameters and real-time operation data into the three-dimensional model of the pipeline corridor; Based on the electrical spatiotemporal evolution function, real-time scenario simulation is performed through the three-dimensional model of the pipeline corridor. Monte Carlo simulation is used to simulate the fire spread process in different scenarios, and the corresponding fire source occurrence point and extinguishing time are recorded; The fire spread process under different scenarios is recorded and the corresponding fire spread heat map is drawn; the simulation results include the fire source point, extinguishing time and fire spread heat map.

6. A method for troubleshooting high-risk electrical fault points in an underground utility corridor according to claim 2, characterized in that: The dispatch of maintenance personnel to inspect and repair high-risk points of electrical faults includes: Feedback the spatial coordinates of the fire source point through the three-dimensional model of the pipeline corridor; Based on each spatial coordinate, calculate the distance between each fire source and each fire door; Determine the danger level of each fire source based on the extinguishing time, distance and fire spread heat map; Based on the danger level, high-risk points of electrical failure are determined; according to the principle of proximity, different maintenance personnel are dispatched to inspect and repair high-risk points of electrical failure.

7. A method for checking high-risk points of electrical faults in underground pipe corridors according to claim 2, characterized in that: Also included is feedback processing, including: Maintenance results and post-maintenance electrical data are uploaded, packaged, and organized in real time, and fed back to the three-dimensional model of the pipeline corridor and the LSTM-Transformer hybrid network. The hyperparameters of the LSTM-Transformer hybrid network are updated in real time, and the structural parameters of the three-dimensional model of the pipeline corridor are updated.

8. A system for checking high-risk electrical fault points in an underground utility gallery, for implementing a method for checking high-risk electrical fault points in an underground utility gallery according to any one of claims 1 to 7, characterized in that: include: Operation environment data acquisition module, used to obtain the operation environment data of the underground integrated pipeline corridor in real time; The operating environment data includes modeling environment parameters, historical sensor data, real-time operating data, historical equipment operation and maintenance management data, and pipe gallery structure parameters; Modeling environment parameters include spatial coordinate information of underground integrated pipeline corridor and comprehensive sensor data; The three-dimensional model construction module of the pipeline corridor is used to construct the three-dimensional model of the pipeline corridor based on the pipeline corridor structural parameters and modeling environment parameters; The electrical spatiotemporal evolution function construction module is used to analyze the electrical evolution laws of underground utility corridors and construct electrical spatiotemporal evolution functions based on historical equipment operation and maintenance management data and historical sensor data; The three-dimensional model simulation module of the utility corridor inputs modeling environment parameters and real-time operation data into the three-dimensional model of the utility corridor based on the electrical time-space evolution function and performs simulation to obtain simulation results; The module for determining high-risk points of electrical faults and planning the elimination paths is used to determine high-risk points of electrical faults based on simulation results; Based on the principle of proximity, maintenance personnel are dispatched to inspect and repair high-risk points of electrical failures.

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