A power distribution network digital and intelligent operation comprehensive management method and system

Abstract

This invention provides a comprehensive digital and intelligent operation and maintenance management method and system for power distribution networks, relating to the field of computer data processing technology. The method includes: S1, obtaining pole and tower information collected by drones during line inspections, performing defect mining and analysis on the pole and tower information, and integrating the analyzed defect information with the pole and tower information to form a pole and tower information collection table; S2, selecting and extracting corresponding data from the pole and tower information collection table, and visualizing the data on a GIS map containing the lines obtained from the pole and tower information collection table using preset markers to generate an inspection status map; S3, statistically classifying the analyzed defect information and matching it through a big data platform to generate a defect repair and management summary table; S4, analyzing the faults using an AI model and a big data platform, combining the inspection status map and the defect repair and management summary table, obtaining priority-ranked repair tasks, and proposing corresponding solutions.

Description

Technical Field

[0001] This invention relates to the field of computer data processing technology, specifically to a comprehensive management method and system for intelligent digital operation and maintenance of power distribution networks. Background Technology

[0002] Since a large number of production and living facilities rely on electricity for operation, whether it is a fire caused by a short circuit, an electric shock accident caused by leakage, or a regional power outage caused by facility failure, all of these can cause significant economic losses. Therefore, the safety and reliability of power generation, transmission, and distribution facilities are of paramount importance to people.

[0003] To maintain the stable operation of power facilities, relevant personnel are usually arranged to conduct regular inspections of power poles and towers. However, manual inspection is very inconvenient and prone to safety problems. Existing technologies have proposed using drones to inspect power poles and towers. This method requires further analysis and processing of the information collected by the drones to obtain various power pole and tower information. How to analyze and process the information collected by the drones and feed it back to the backend processing unit for maintenance is a problem that this invention needs to address. Summary of the Invention

[0004] The purpose of this invention is to provide a comprehensive digital and intelligent operation and maintenance management method and system for power distribution networks. It utilizes drones to inspect power poles and towers, obtaining more intuitive inspection status diagrams. The collected tower information is then processed for defect analysis, resulting in a more comprehensive summary table of defect repair and management. This invention combines the inspection status diagrams and the defect repair and management summary table to perform fault analysis and prioritize maintenance tasks.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following solution:

[0006] A comprehensive digital and intelligent operation and maintenance management method for power distribution networks includes:

[0007] S1. Obtain pole and tower information collected by the UAV during line inspection, perform defect mining and analysis on the pole and tower information, and integrate the analyzed defect information with the pole and tower information to form a pole and tower information collection table.

[0008] S2. Select and extract the corresponding data from the pole information collection table, and visualize the data on the GIS map containing the line obtained from the pole information collection table through preset markers to generate an inspection status map.

[0009] S3. Statistically classify the defect information obtained from the analysis, and generate a summary table of defect inspection and treatment through the big data platform;

[0010] S4. Through AI model and big data platform analysis, combined with inspection status map and defect repair and management summary table, fault analysis is carried out to obtain priority-ranked maintenance tasks and propose corresponding solutions.

[0011] A further preferred technical solution is that the inspection status diagram includes a geographical wiring diagram, a primary wiring diagram, and a defect distribution diagram;

[0012] The specific process for generating the inspection status diagram is as follows:

[0013] Extract the location data corresponding to the poles from the pole information collection table, visualize the location data on the GIS map containing the lines obtained from the pole information collection table through preset markers, and generate a geographic connection diagram.

[0014] Extract the connection method of the primary equipment corresponding to the pole from the pole information collection table, visualize the connection method of the primary equipment on the GIS map containing the line obtained from the pole information collection table through preset marks, and generate a primary wiring diagram;

[0015] Extract the corresponding defect information of the poles from the pole information collection table, visualize the defect information on the GIS map containing the line obtained from the pole information collection table through preset markers, and generate a defect distribution map.

[0016] A further preferred technical solution is to perform defect mining and analysis on the tower information. The obtained defect information is associated with the tower name. The defect information includes the defect target corresponding to the tower name, component type, component defect description, defect classification, and defect nature. The process of generating a defect inspection and treatment summary table is as follows:

[0017] The defect inspection and management summary table is defined in advance, with the line name as the column header of each row. Based on the line name, the defect information of each pole and tower on the line is counted, and the defect target, component type, component defect description, defect classification, and defect nature corresponding to the pole and tower name are stored in each row.

[0018] A further optimized technical solution involves obtaining the priority-ranked maintenance tasks as follows: Through AI model and big data platform analysis, combined with the geographical wiring diagram, primary wiring diagram, defect distribution map, and defect maintenance and management summary table, multi-dimensional fault analysis is performed on each row's corresponding defect target, component type, component defect description, defect classification, and defect nature. This analysis yields the defect level and impact range of each row's defect information in the defect maintenance and management summary table, and generates maintenance tasks. The maintenance tasks are then prioritized based on their defect level and impact range.

[0019] A further preferred technical solution is that when the drone inspects the line, it takes pictures of the towers in the order of their hierarchical structure, collects and analyzes the information of the towers in the pictures to obtain tower information, and performs defect detection on the pictures, marking defect targets on the pictures with detection boxes, and collects and analyzes the information of the defect targets in the pictures to obtain defect information.

[0020] A further preferred technical solution is that the process of integrating the analyzed defect information with the tower information to form a tower information collection table is as follows:

[0021] The table is predefined, and the corresponding tower information is stored in each row according to the hierarchical order of the towers in the line. The tower name in the tower information is used as the column header of each column in each row, and the latitude and longitude coordinates in the tower information are stored in other columns.

[0022] Add a column to the table, which is defined as the name of the superior tower. Find the name of the superior tower corresponding to the tower name in each row according to the order of the towers in the line, and fill it into the column.

[0023] Find the name and latitude / longitude coordinates of the superior tower in each row of the table, and use the latitude / longitude coordinates as the end coordinate point; locate the row containing the superior tower name and extract the corresponding latitude / longitude coordinates, and use the latitude / longitude coordinates as the start coordinate point.

[0024] Modify the definition of latitude and longitude coordinates in each row of the pole information collection table to the end coordinates; and add a column to the table, which is defined as the starting coordinates. Then connect the starting coordinates and the ending coordinates in each row to form a latitude and longitude line segment, thus obtaining the pole information collection table.

[0025] A further preferred technical solution is that the process of generating a geographic connection map is as follows: extract the latitude and longitude line segments corresponding to the poles from the pole information collection table, map the latitude and longitude line segments onto the GIS map, and connect several latitude and longitude line segments on the GIS map to form a line, thus forming a geographic connection map.

[0026] A further preferred technical solution is that the process of collecting and analyzing information on defective targets in captured images to obtain defect information is as follows:

[0027] The system extracts images of defective targets corresponding to poles from the pole identification information database, analyzes the defective targets in the images to obtain the component types and defect descriptions of the defective targets;

[0028] By classifying the types of components, the defect categories corresponding to the defect targets are obtained;

[0029] The defect nature determination conditions corresponding to the component type are invoked, and the component defect description is analyzed and determined according to the defect nature determination conditions to obtain the defect nature corresponding to the defect target.

[0030] A further preferred technical solution is that the process of generating the defect distribution map is as follows:

[0031] Obtain a defect summary table by performing defect data mining and analysis on the pole and tower identity information database. Extract the defect classification and defect nature corresponding to the pole and tower from the defect summary table. Then, package the component types and defect nature corresponding to the pole and tower according to the same defect classification to form defect classification data.

[0032] Based on the first weight value corresponding to the defect nature, the same defect classification data are fused into a first defect degree, and the result of the first defect degree fusion is displayed at the towers on the power facility geographical wiring map through different color markers to form a first line defect distribution map.

[0033] The defect data is fused into a second defect degree based on the first weight value corresponding to the defect nature and the second weight value corresponding to the defect classification. The result of the second defect degree fusion is displayed on the towers on the power facility geographic wiring map using different colored markers to form a second line defect distribution map.

[0034] Different first-line defect distribution maps are generated based on different defect classifications. The first-line defect distribution map is used to show the degree of defect of the towers on the GIS map under the same defect classification. The second-line defect distribution map is used to show the degree of defect of the towers on the GIS map under the overall situation.

[0035] A digital and intelligent operation and maintenance integrated management system for power distribution networks, applying the aforementioned digital and intelligent operation and maintenance integrated management method for power distribution networks, includes:

[0036] Pole and Tower Information Collection Table Generation Module: Obtains pole and tower information collected by UAVs during line inspection, performs defect mining and analysis on the pole and tower information, and integrates the analyzed defect information with the pole and tower information to form a pole and tower information collection table;

[0037] Inspection status map generation module: Select and extract the corresponding data from the pole information collection table, visualize the data on the GIS map containing the line obtained from the pole information collection table through preset marks, and generate an inspection status map.

[0038] Defect Repair and Management Summary Table Generation Module: Statistically classifies the defect information obtained from the analysis, and matches it through the big data platform to generate a defect repair and management summary table;

[0039] Maintenance module: Through AI model and big data platform analysis, combined with inspection status map and defect maintenance summary table, fault analysis is carried out to obtain priority maintenance tasks and propose corresponding solutions.

[0040] The beneficial effects of this invention are:

[0041] This invention provides a comprehensive digital and intelligent operation and maintenance management method and system for power distribution networks. It primarily utilizes drones for line inspections, collecting information on poles and towers along the lines. The system then uses diagrams to display various data points of the power distribution network along the lines, including the geographical distribution of poles and towers, defect distribution, and primary equipment distribution. Through secondary data mining, it can generate maintenance tasks and material lists, which are then provided to the backend processing unit, allowing it to intuitively view the operational status of the power facilities along the lines. Furthermore, relying on AI models and big data platform analysis, it outputs six major data results: pole and tower information collection tables, primary wiring diagrams, defect distribution maps, maintenance strategies, and material lists. This provides visualized decision support for defect elimination during maintenance, pole and tower optimization, and material management, promoting the transformation of power distribution network management from experience-driven to data-driven. It constructs a governance system of "data collection - AI analysis - dynamic decision-making - closed-loop execution," achieving deep integration of multi-source data in the power distribution network, intelligent linkage between operation and maintenance strategies and material lists, and closed-loop auditing of maintenance results and material consumption. Attached Figure Description

[0042] Figure 1 This is a flowchart illustrating the intelligent digital operation and maintenance integrated management method for power distribution networks in Embodiment 1 of the present invention.

[0043] Figure 2 This is a schematic diagram of the geographical connection diagram in Embodiment 1 of the present invention;

[0044] Figure 3 This is a schematic diagram of the circuit defect distribution in Embodiment 1 of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0047] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0048] Furthermore, for clarity and brevity, descriptions of well-known structures, functions, and configurations may have been omitted. Those skilled in the art will recognize that various changes and modifications can be made to the examples described herein without departing from the spirit and scope of this disclosure.

[0049] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0050] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0051] The present invention will now be described in detail with reference to the accompanying drawings and embodiments:

[0052] Example 1

[0053] At present, distribution network assets account for about 55% of power grid assets. With the increasing scale of assets, the traditional management model faces the following problems: (1) Wide distribution of equipment and complex terrain: low efficiency of manual inspection and insufficient coverage of equipment management in high-risk areas; (2) Serious data silos: equipment ledgers, defect status, maintenance plans and material data are scattered and no linkage analysis is carried out; (3) Insufficient data visualization: cannot intuitively reflect the distribution of line defects, equipment status and disaster risks; (4) Delayed decision-making: relying on experience-driven, maintenance strategies and material allocation lack data support, resulting in inefficient operation and maintenance.

[0054] To address the aforementioned problems, this invention proposes a comprehensive digital and intelligent operation and maintenance management method for power distribution networks, such as... Figure 1 As shown, the integrated management method for intelligent digital operation and maintenance of power distribution networks includes the following steps:

[0055] S1. Obtain pole and tower information collected by the UAV during line inspection, perform defect mining and analysis on the pole and tower information, and integrate the analyzed defect information with the pole and tower information to form a pole and tower information collection table.

[0056] S2. Select and extract the corresponding data from the pole information collection table, and visualize the data on the GIS map containing the line obtained from the pole information collection table through preset markers to generate an inspection status map.

[0057] S3. Statistically classify the defect information obtained from the analysis, and generate a summary table of defect inspection and treatment through the big data platform;

[0058] S4. Through AI model and big data platform analysis, combined with inspection status map and defect repair and management summary table, fault analysis is carried out to obtain priority-ranked maintenance tasks and propose corresponding solutions.

[0059] A further preferred technical solution is that when the drone inspects the line, it takes pictures of the towers in the order of their hierarchical structure, collects and analyzes the information of the towers in the pictures to obtain tower information, and performs defect detection on the pictures, marking defect targets on the pictures with detection boxes, and collects and analyzes the information of the defect targets in the pictures to obtain defect information.

[0060] The pole information includes pole name, latitude and longitude coordinates, photo time, voltage level, line name, turning angle, altitude, pole type, span, total number of defects, tree obstructions, guy wire insulation, ancillary facilities, number of guy wires, license plate status, conductor type, number of circuits, conductor joints, pole material, crossing area, guy wire model, insulator type, geographical environment, three-wire connection, high and low voltage on the same pole, and conductor model. The latitude and longitude coordinates are composed of longitude and latitude.

[0061] The defect information includes the defect classification, defect nature, component type, and component defect description corresponding to the defect target. A further preferred technical solution is that the process of obtaining defect information by collecting and analyzing information from the captured images of the defect target is as follows:

[0062] The system extracts images of defective targets corresponding to poles from the pole identification information database, analyzes the defective targets in the images to obtain the component types and defect descriptions of the defective targets;

[0063] By classifying the types of components, the defect categories corresponding to the defect targets are obtained;

[0064] The defect nature determination conditions corresponding to the component type are invoked, and the component defect description is analyzed and determined according to the defect nature determination conditions to obtain the defect nature corresponding to the defect target.

[0065] When using drones to inspect power poles, the backend processing unit receives images taken by the drones, along with the corresponding time and location information. The images can be tagged using the time and location information, and the status of the power poles can be collected by analyzing the images. The backend processing unit then obtains the current power pole information and uses this information to maintain the power facilities.

[0066] Based on this, in existing technologies, since drones have their own positioning devices, namely GPS positioning, when uploading images to the backend processing terminal, the drone also uploads the location of the drone when the image was taken. This location information is the longitude x and latitude y obtained through GPS, that is, the longitude and latitude point (x, y).

[0067] When using drones to inspect power poles, the position of the power pole is usually marked using latitude and longitude points (x, y). Once the position of the power pole is marked, it can be substituted into a GIS map, i.e., marked on the GIS map. However, after substituted into the GIS map, only the position of the power pole itself can be obtained. Since the latitude and longitude points (x, y) are point data, they cannot reflect direction. Therefore, the route cannot be directly formed on the GIS map. Staff need to manually import the route or connect the lines in order to display the drone inspection route on the GIS map. This operation is quite cumbersome.

[0068] To address the aforementioned issues, this invention proposes a preprocessing design scheme for latitude and longitude coordinates. This preprocessing involves modifying the latitude and longitude coordinates into line segments based on the associated coordinates and inspection results before mapping the tower information onto the GIS map. These line segments are composed of the latitude and longitude coordinates of the towers above and below, establishing a "tower-latitude and longitude line segment" relationship. When mapping these line segments onto the GIS map according to this relationship, several line segments can be directly connected on the GIS map to form a line. This eliminates the need for further judgment on the connections between latitude and longitude coordinates, thus improving the efficiency of generating geographical wiring diagrams for power facilities.

[0069] Furthermore, this invention uses the GPS positioning uploaded when the drone takes pictures as the location of the pole. In actual operation, in order to collect accurate location information, the drone can be operated to hover directly above the pole, and the GPS positioning uploaded by the drone when it takes pictures directly above the pole can be used as the latitude and longitude of the pole.

[0070] A further preferred technical solution is that the process of integrating the analyzed defect information with the tower information to form a tower information collection table is as follows:

[0071] The table is predefined, and the corresponding tower information is stored in each row according to the hierarchical order of the towers in the line. The tower name in the tower information is used as the column header of each column in each row, and the latitude and longitude coordinates in the tower information are stored in other columns.

[0072] Add a column to the table, which is defined as the name of the superior tower. Find the name of the superior tower corresponding to the tower name in each row according to the order of the towers in the line, and fill it into the column.

[0073] Find the name and latitude / longitude coordinates of the superior tower in each row of the table, and use the latitude / longitude coordinates as the end coordinate point; locate the row containing the superior tower name and extract the corresponding latitude / longitude coordinates, and use the latitude / longitude coordinates as the start coordinate point.

[0074] Modify the definition of latitude and longitude coordinates in each row of the pole information collection table to the end coordinates; and add a column to the table, which is defined as the starting coordinates. Then connect the starting coordinates and the ending coordinates in each row to form a latitude and longitude line segment, thus obtaining the pole information collection table.

[0075] As can be seen, the pole information collection table proposed in this invention is a pre-processed table containing the latitude and longitude line segments corresponding to the poles. The latitude and longitude line segments are composed of the latitude and longitude coordinate points of the upper and lower level poles. The acquisition process is as follows: based on the associated latitude and longitude coordinate points and inspection results, the latitude and longitude coordinate points in the pole information are modified into latitude and longitude line segments in advance, thus establishing the association relationship of "pole-latitude and longitude line segments". When the pole information collection table is directly imported into the GIS map generation software, the latitude and longitude line segments and pole positions are directly mapped onto the GIS map according to the association relationship of "pole-latitude and longitude line segments". Several latitude and longitude line segments can be directly connected on the GIS map to form lines. The GIS map generation software does not need to make further judgments on the connection between latitude and longitude coordinate points, which can improve the generation efficiency of the power facility geographic wiring diagram.

[0076] A further preferred technical solution is that the inspection status diagram includes a geographical wiring diagram, a primary wiring diagram, and a defect distribution diagram. It can be seen that the present invention mainly uses drawings to display various data of the power distribution network on the line. The visualization of the data makes it easy for the back-end processing terminal to intuitively see the operation status of the power facilities on the line.

[0077] Based on the above, the process of generating the inspection status map is as follows:

[0078] Extract the location data corresponding to the poles from the pole information collection table, visualize the location data on the GIS map containing the lines obtained from the pole information collection table through preset markers, and generate a geographic connection diagram.

[0079] Extract the connection method of the primary equipment corresponding to the pole from the pole information collection table, visualize the connection method of the primary equipment on the GIS map containing the line obtained from the pole information collection table through preset marks, and generate a primary wiring diagram;

[0080] Extract the corresponding defect information of the poles from the pole information collection table, visualize the defect information on the GIS map containing the line obtained from the pole information collection table through preset markers, and generate a defect distribution map.

[0081] Specifically, the process of generating a geographic connection map is as follows: The latitude and longitude segments corresponding to the poles are extracted from the pole information collection table; these segments are mapped onto a GIS map; and several latitude and longitude segments are connected on the GIS map to form a route, thus creating a geographic connection map. Figure 2 As shown, various auxiliary facilities in the tower information are then displayed on the geographic wiring diagram using different preset markers.

[0082] Specifically, the process of generating a primary wiring diagram is as follows: The latitude and longitude segments corresponding to the poles are extracted from the pole information collection table, mapped onto a GIS map, and connected to form a line. Then, the connection methods of the primary equipment corresponding to the poles are extracted from the pole information collection table, providing a visual representation of the connection methods and topology of the primary equipment in the power system. The line operation structure is fed back to the design end. By parsing the line's structural blueprint, the diagram is compared with the design drawing for consistency, providing the owner with a guide for operation, maintenance, and verification. Furthermore, when a line fault occurs, the faulty equipment and its impact range can be quickly located through the line protection action signals and the primary wiring diagram structure. Before power outage maintenance, the optimal isolation path can be quickly determined by analyzing the position logic of circuit breakers and disconnectors in the primary wiring diagram, ensuring the stable operation of the power system.

[0083] A further preferred technical solution is to perform defect mining and analysis on the tower information. The obtained defect information is associated with the tower name. The defect information includes the defect target corresponding to the tower name, component type, component defect description, defect classification, and defect nature. The process of generating a defect inspection and treatment summary table is as follows:

[0084] The defect inspection and management summary table is defined in advance, with the line name as the column header of each row. Based on the line name, the defect information of each pole and tower on the line is counted, and the defect target, component type, component defect description, defect classification, and defect nature corresponding to the pole and tower name are stored in each row.

[0085] A further preferred technical solution is that the process of generating the defect distribution map is as follows:

[0086] Obtain a defect summary table by performing defect data mining and analysis on the pole and tower identity information database. Extract the defect classification and defect nature corresponding to the pole and tower from the defect summary table. Then, package the component types and defect nature corresponding to the pole and tower according to the same defect classification to form defect classification data.

[0087] Based on the first weight value corresponding to the defect nature, the same defect classification data are fused into a first defect degree, and the result of the first defect degree fusion is displayed at the towers on the power facility geographical wiring map through different color markers to form a first line defect distribution map.

[0088] The defect data is fused into a second defect degree based on the first weight value corresponding to the defect nature and the second weight value corresponding to the defect classification. The result of the second defect degree fusion is displayed on the towers on the power facility geographic wiring map using different colored markers to form a second line defect distribution map.

[0089] Different first-line defect distribution maps are generated based on different defect classifications. The first-line defect distribution map is used to show the degree of defect of the towers on the GIS map under the same defect classification. The second-line defect distribution map is used to show the degree of defect of the towers on the GIS map under the overall situation.

[0090] The first defect degree fusion process is as follows: obtain the preset base number of the current defect classification, extract all defect classification data of a pole with the same defect classification as the current defect classification, obtain the first weight value corresponding to the defect nature in all defect classification data, sum all the first weight values, multiply the sum by the preset base number, and obtain the result of the first defect degree fusion of a pole, and so on.

[0091] The second defect degree fusion process is as follows: obtain the first weight value corresponding to the defect nature and the second weight value corresponding to the defect classification, extract all defect data in a tower, multiply the first weight value corresponding to the defect nature and the second weight value corresponding to the defect classification in turn, sum the results of the multiplication, and obtain the second defect degree fusion result of a tower, and so on.

[0092] Specifically, since power poles in real-world scenarios have many types of components, including tension clamps, conductors, and signs, and different maintenance strategies are required for defects in different component types, this application considers component types and their corresponding defect descriptions. By analyzing component types and defect descriptions, the nature of the defect corresponding to the current component type can be determined. This determination process involves calling the defect nature judgment conditions corresponding to the component type for analysis and judgment, determining whether the defect nature is a general defect / serious defect / critical defect. The defect nature judgment conditions are standard conditions and will not be elaborated here. This invention allows the present invention to obtain the defect severity of the component type corresponding to the defect target on the power pole. By integrating the defect severity of all component types on the power pole, the overall defect level of the current power pole can be obtained. The different overall defect levels corresponding to different power poles are displayed on a GIS map using different color markers, allowing staff to intuitively see the defects of the power pole and providing decision support for defect elimination and power pole optimization.

[0093] In real-world scenarios, after analyzing the types of defective components, eight typical application scenarios were identified. These components were then categorized into eight major types, as described in this embodiment: hardware, poles, insulators, auxiliary facilities, conductors, channel environment, foundations, and grounding devices. Furthermore, defect analysis of different component types within the same defect category can be mutually influential. Therefore, this invention proposes two types of line defect distribution maps: one integrates the defect severity of all component types on the pole, visually representing the overall defect severity of the pole; the other pre-classifies component types on the pole for different application scenarios, integrating the defect severity of component types belonging to the same defect category on the pole, visually representing the predominant defect severity of the pole in different application scenarios, providing customers with diverse options suitable for various application scenarios.

[0094] Specifically, the nature of the defect includes general defects, serious defects, and critical defects. Different first weight values can be set in advance for different defect natures under different defect classifications. At this time, the first weight values of the same defect nature under different defect classifications can be the same or different. For example, general defects are uniformly set as q1, serious defects are set as q2, and critical defects are set as q3, and q1 < q2 < q3. The first defect degree fusion is performed on the defect classification data according to the first weight value corresponding to the defect nature. Since the same defect classification is targeted at this time, the same base number a can be set. The first defect degree fusion is to add the first weight values of the defect targets corresponding under the same defect classification, and multiply the sum by the same base number a. For example: in an application scenario with a base number of a, Tower A has two defect targets, which respectively correspond to general defects and serious defects. Then, through the first defect degree fusion, a*(q1 + q2) is obtained; Tower B has two defect targets, which respectively correspond to general defects and critical defects. Then, through the first defect degree fusion, a*(q1 + q3) is obtained. It can be seen that a*(q1 + q2) < a*(q1 + q3). Then, the different degrees of defects of Tower A and Tower B in this application scenario can be displayed on the GIS map through different color markings.

[0095] Based on the above principle, the process of the second defect degree fusion can be obtained. Different second weight values are set for different defect classifications, and different defect classifications are substituted into the calculation process, that is, different base numbers can be set, and the defect degree of the tower under the overall situation can be obtained. Specifically, as Figure 3 shown, at this time, the line defect distribution map is the first line defect distribution map, which shows the defect degree of the tower when the defect classification is fittings; the second line defect distribution map shows the defect degree of the tower under the overall situation. Through different color markings and explanations of the color markings below, the staff can intuitively see the defects of the tower, providing decision-making support for defect elimination and auxiliary optimization of the tower. Moreover, the偏重defect degree of the tower in different application scenarios can be visually displayed, providing diverse choices for customers and generating maintenance strategies.

[0096] Finally, through the analysis of the AI model and the big data platform, combined with the defect targets, component types, component defect descriptions, defect classifications, and defect natures corresponding to each row in the geographical connection diagram, primary connection diagram, defect distribution map, and defect maintenance and governance summary table, multi-dimensional fault analysis is carried out to analyze the defect level and influence range of each row of defect information in the defect maintenance and governance summary table, and generate maintenance tasks; the maintenance tasks are prioritized according to the defect level and influence range. The purpose is to propose special treatments such as live working and power outage for the maintenance key points, reasonably analyze the maintenance key points from multiple dimensions, and put forward the specific work arrangements, material allocations, and personnel configurations in the maintenance solution. It should be noted that there may be an incorrect expression "偏重" in the original text which might need to be corrected according to the actual context for a more accurate translation.

[0097] Based on this, the comprehensive governance method of digital and intelligent operation and maintenance of distribution networks is specifically applied to 10kV distribution networks and 0.4kV low-voltage lines. Through the output of tower information collection forms, geographical wiring diagrams, primary wiring diagrams, defect distribution maps, maintenance strategies, and material lists, the method deeply integrates digital and intelligent operation and maintenance with traditional data, achieving the distribution network data governance effect of "AI empowerment, drawing collaboration platform, precise maintenance navigation, and full-cycle management".

[0098] Example 2

[0099] A digital and intelligent operation and maintenance integrated management system for power distribution networks, applying the aforementioned digital and intelligent operation and maintenance integrated management method for power distribution networks, includes:

[0100] Pole and Tower Information Collection Table Generation Module: Obtains pole and tower information collected by UAVs during line inspection, performs defect mining and analysis on the pole and tower information, and integrates the analyzed defect information with the pole and tower information to form a pole and tower information collection table;

[0101] Inspection status map generation module: Select and extract the corresponding data from the pole information collection table, visualize the data on the GIS map containing the line obtained from the pole information collection table through preset marks, and generate an inspection status map.

[0102] Defect Repair and Management Summary Table Generation Module: Statistically classifies the defect information obtained from the analysis, and matches it through the big data platform to generate a defect repair and management summary table;

[0103] Maintenance module: Through AI model and big data platform analysis, combined with inspection status map and defect maintenance summary table, fault analysis is carried out to obtain priority maintenance tasks and propose corresponding solutions.

[0104] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Based on the technical essence of the present invention, any simple modifications, equivalent substitutions, and improvements made to the above embodiments within the spirit and principles of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A power distribution network digital and intelligent operation comprehensive management method, characterized in that, The method comprises the following steps: S1, obtaining tower information collected by a UAV when patrolling a line, mining and analyzing defects of the tower information, and integrating the analyzed defect information and the tower information to form a tower information collection table; When the UAV patrols the line, the UAV takes pictures of the towers in the line according to the superior-inferior order of the towers in the line, collects and analyzes information of the towers in the pictures to obtain tower information, and detects defects in the pictures to mark the defect targets in the pictures with detection boxes, and collects and analyzes information of the defect targets in the pictures to obtain defect information; S2, selecting and extracting corresponding data from the tower information collection table, and visualizing the data on a GIS map containing the line obtained through the tower information collection table by a preset mark to generate a patrol status map; The patrol status map comprises a defect distribution map, and the process of generating the defect distribution map comprises the following steps: Obtaining a defect summary table obtained by mining and analyzing defect data from the tower information collection table, extracting the defect classification and defect properties corresponding to the towers from the defect summary table, and packaging the component types and defect properties corresponding to the towers according to the same defect classification to form defect classification data; According to the first weight value corresponding to the defect property, the same defect classification data is subjected to first defect degree fusion, and the result of the first defect degree fusion is displayed on the towers on the power facility geographical connection diagram by marks of different colors to form a first line defect distribution map; According to the first weight value corresponding to the defect property and the second weight value corresponding to the defect classification, the defect data is subjected to second defect degree fusion, and the result of the second defect degree fusion is displayed on the towers on the power facility geographical connection diagram by marks of different colors to form a second line defect distribution map; Then, different first line defect distribution maps are formed according to different defect classifications, and the first line defect distribution maps are used to display the defect degree of the towers on the GIS map under the same defect classification, and the second line defect distribution maps are used to display the defect degree of the towers on the GIS map as a whole; S3, statistically classifying the analyzed defect information, and matching through a big data platform to generate a defect repair and management summary table; S4, analyzing through an AI model and a big data platform, combining the patrol status map and the defect repair and management summary table to analyze faults, obtaining a priority-ordered repair task, and proposing a corresponding solution.

2. The power distribution network digitalization operation comprehensive management method according to claim 1, characterized in that, The patrol status map comprises a geographical connection diagram, a primary connection diagram, and a defect distribution map; Then, the process of generating the patrol status map comprises the following steps: Extracting position data corresponding to the towers from the tower information collection table, and visualizing the position data on a GIS map containing the line obtained through the tower information collection table by a preset mark to generate a geographical connection diagram; Extracting connection modes of primary equipment corresponding to the towers from the tower information collection table, and visualizing the connection modes of the primary equipment on a GIS map containing the line obtained through the tower information collection table by a preset mark to generate a primary connection diagram; Extract the defect information corresponding to the tower from the tower information collection table, and visualize the defect information on the GIS map containing the line obtained by the tower information collection table through the preset mark to generate a defect distribution map.

3. The power distribution network digitalization operation comprehensive management method according to claim 2, characterized in that, The defect information obtained by defect mining and analysis of the tower information is associated with the tower name, and the defect information includes the defect target, component type, component defect description, defect classification, and defect nature corresponding to the tower name. The process of generating a defect maintenance management summary table is as follows: The defect maintenance management summary table is defined in advance, the line name is used as the column header of each column in each row, the defect information of each tower on the line is counted according to the line name, and the defect target, component type, component defect description, defect classification, and defect nature corresponding to the tower name are stored in each row.

4. The power distribution network digitalization operation comprehensive management method according to claim 3, characterized in that, The process of obtaining the priority-ordered maintenance tasks is as follows: through AI model and big data platform analysis, combined with the geographic connection diagram, the primary connection diagram, the defect distribution map, and the defect target, component type, component defect description, defect classification, and defect nature corresponding to each row in the defect maintenance management summary table, multi-dimensional fault analysis is performed, the defect level and influence range of each row of defect information in the defect maintenance management summary table are analyzed, and a maintenance task is generated; the maintenance tasks are prioritized according to the defect level and influence range.

5. The power distribution network digitalization operation comprehensive management method according to claim 2, characterized in that, The process of integrating the analyzed defect information and tower information to form a tower information collection table is as follows: The table is defined in advance, the tower information corresponding to the tower in the line is stored in each row in order according to the superior-inferior order, the tower name in the tower information is used as the column header of each column in each row, and the latitude and longitude coordinates in the tower information are stored in other columns; A column is added to the table, which is defined as the superior tower name, and the superior tower name corresponding to the tower name in each row is found according to the superior-inferior order of the tower in the line and filled into the column; The superior tower name and latitude and longitude coordinate point are found in each row of the table, and the latitude and longitude coordinate point is taken as the end coordinate point; The corresponding latitude and longitude coordinate point is extracted according to the superior tower name to locate the row, and the latitude and longitude coordinate point is taken as the starting coordinate point; The definition of the latitude and longitude coordinate point in each row of the tower information collection table is modified to the end coordinate point; and a column is added to the table, which is defined as the starting coordinate point, then the starting coordinate point and the end coordinate point in each row are connected to form a latitude and longitude line segment, and the tower information collection table is obtained.

6. The power distribution network digitalization operation comprehensive management method according to claim 5, characterized in that, The process of generating a geographic connection diagram is as follows: extract the latitude and longitude line segment corresponding to the tower from the tower information collection table, map the latitude and longitude line segment on the GIS map, connect the latitude and longitude line segments on the GIS map to form a line, and form a geographic connection diagram.

7. The power distribution network digitalization operation comprehensive management method according to claim 1, characterized in that, The process of obtaining defect information by analyzing the defect target in the photographed picture is as follows: The photographed picture with the defect target corresponding to the tower in the tower information collection table is mined, and the defect target in the photographed picture is analyzed to obtain the component type and component defect description corresponding to the defect target; The component type is classified to obtain the defect classification corresponding to the defect target; The defect nature determination conditions corresponding to the component type are invoked, and the component defect description is analyzed and determined according to the defect nature determination conditions to obtain the defect nature corresponding to the defect target.

8. A power distribution network digital and intelligent operation comprehensive management system, characterized in that, The application of the intelligent digital operation and maintenance integrated management method for power distribution networks as described in any one of claims 1-7 includes: Pole and Tower Information Collection Table Generation Module: Obtains pole and tower information collected by UAVs during line inspection, performs defect mining and analysis on the pole and tower information, and integrates the analyzed defect information with the pole and tower information to form a pole and tower information collection table; Inspection status map generation module: Select and extract the corresponding data from the pole information collection table, visualize the data on the GIS map containing the line obtained from the pole information collection table through preset marks, and generate an inspection status map. Defect Repair and Management Summary Table Generation Module: Statistically classifies the defect information obtained from the analysis, and matches it through the big data platform to generate a defect repair and management summary table; Maintenance module: Through AI model and big data platform analysis, combined with inspection status map and defect maintenance summary table, fault analysis is carried out to obtain priority maintenance tasks and propose corresponding solutions.

Images