Substation three-dimensional design model and intelligent patrol system

Abstract

The invention discloses a transformer substation three-dimensional design model and intelligent patrol system. The system comprises a transformer substation three-dimensional fine design module, an intelligent patrol planning and control module and a data processing and analysis module, wherein the transformer substation three-dimensional fine design module realizes data interaction through a data interface; the transformer substation three-dimensional fine design module is used for constructing a three-dimensional model of a transformer substation, ensuring that a spatial feature error between the three-dimensional model and actual equipment is smaller than a preset threshold value through a precision verification mechanism, and updating the three-dimensional model based on the equipment change information and an abnormal judgment result output by the data processing and analysis module; the intelligent patrol planning and control module is used for planning a patrol path of patrol equipment on the basis of the three-dimensional model and controlling the patrol equipment to execute patrol operation so as to collect equipment state data; and the data processing and analyzing module is used for processing the equipment state data, calculating and judging the equipment abnormity, and feeding back to the substation three-dimensional fine design module to provide a basis for updating the three-dimensional model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of substation design and operation and maintenance, and particularly relates to a three-dimensional design model of a substation and an intelligent inspection system. BACKGROUND

[0002] As the core hub of the power system, the safe and stable operation of the substation is directly related to the reliability of the power grid. With the transformation of the power system to intelligentization and digitization, the traditional substation design and operation and maintenance mode gradually exposes many deficiencies. In the design stage, the early two-dimensional drawing design method is difficult to intuitively reflect the spatial layout and complex connection relationship of the equipment, resulting in a high design error rate, and problems such as equipment installation interference and insufficient maintenance access often occur, increasing the construction rework cost and the difficulty of later operation and maintenance. Although three-dimensional modeling technology has been applied in substation design in recent years, the existing models are mostly limited to rough display of the geometric appearance, and the integration of key information such as physical parameters and electrical characteristics of the equipment is low, and the model precision cannot meet the needs of refined operation and maintenance, especially in the expression of the spatial position relationship of complex equipment.

[0003] In terms of operation and maintenance inspection, the traditional manual inspection method is limited by the professional level, work experience and on-site environment of the inspection personnel, and has problems such as low inspection efficiency, high missed and mistaken detection rate, and non-standard data recording. Although some substations have introduced intelligent inspection equipment such as drones and robots, the path planning of the existing inspection systems mostly relies on preset coordinate points or simple environment maps, and lacks deep integration with the substation design model, resulting in insufficient rationality of the inspection path planning and comprehensiveness of the equipment coverage. At the same time, the processing and analysis of the inspection data mostly use single threshold judgment or manual experience review, and the ability to identify early potential faults of the equipment is limited, and a large amount of inspection data cannot effectively feed back to the design link, forming a data island between design and operation and maintenance, and it is difficult to realize the collaborative optimization of the whole life cycle. In addition, the long-term operation of the substation equipment will cause changes in its parameter characteristics and spatial position, and the existing design model lacks a synchronous updating mechanism with the actual equipment state, further exacerbating the disconnection between design and operation and maintenance. SUMMARY

[0004] In view of the defects and deficiencies of the prior art, the present application provides a transformer substation three-dimensional design model and intelligent patrol system, aiming to solve the problems of low precision of traditional two-dimensional design, poor efficiency of manual patrol and loose combination of existing three-dimensional design and intelligent patrol technology. The system includes a transformer substation three-dimensional fine design module, an intelligent patrol planning and control module and a data processing and analysis module which realize data interaction through a data interface, forming a technical closed loop of "design-patrol-analysis-update". Among them, the transformer substation three-dimensional fine design module collects the geometric parameters, physical parameters and electrical parameters of the equipment through a laser scanner, a high-definition camera and a sensor acquisition device, constructs a three-dimensional model and ensures that the spatial characteristics (including geometric size, relative position and topological relationship) of the model and the actual equipment meet the preset requirements through precision verification, and dynamically updates the model based on the equipment change information and the abnormal judgment results of the data processing and analysis module; the intelligent patrol planning and control module plans the patrol path based on the high-precision three-dimensional model, adopts the improved A* algorithm and combines the motion characteristics of the patrol equipment (including unmanned aerial vehicles and robots, among which the unmanned aerial vehicle model is DJIMatrice 350 RTK with positioning accuracy of ±0.1m), controls the equipment to perform patrol operation, and monitors the battery capacity, temperature and sensor working state of the equipment in real time, and performs emergency operations such as returning, reducing speed or emergency landing according to the preset threshold; the data processing and analysis module processes the patrol data by combining data cleaning, filtering processing and data normalization, extracts characteristic parameters such as equipment appearance, temperature and vibration, judges equipment abnormalities by calculating the deviation rate of the characteristic parameters, divides the abnormality levels into mild, moderate and severe according to the deviation degree, and outputs the diagnosis results in the form of text report, chart or three-dimensional model annotation and stores them in the database, and feeds back the abnormal results to the three-dimensional fine design module to provide basis for model updating. Through the organic linkage of the three modules, the system realizes the seamless connection of transformer substation design and operation and maintenance, improves the design precision, patrol efficiency and abnormal diagnosis accuracy, and ensures the safe and stable operation of the transformer substation.

[0005] The present application specifically adopts the following technical solutions:

[0006] A transformer substation three-dimensional design model and intelligent patrol system, comprising:

[0007] A transformer substation three-dimensional fine design module, an intelligent patrol planning and control module and a data processing and analysis module which realize data interaction through a data interface;

[0008] The transformer substation three-dimensional fine design module is used to construct a three-dimensional model of the transformer substation, and a precision verification mechanism is used to ensure that the spatial characteristics error of the three-dimensional model and the actual equipment is less than a preset threshold, the spatial characteristics including the geometric size, relative position and topological relationship of the equipment; and the three-dimensional model is updated based on the equipment change information and the abnormal judgment results output by the data processing and analysis module;

[0009] The intelligent inspection planning and control module is used to plan the inspection path of the inspection equipment based on the three-dimensional model, and control the inspection equipment to perform inspection operations to collect equipment status data.

[0010] The data processing and analysis module is used to process equipment status data, extract equipment feature parameters, and determine equipment anomalies by calculating the feature parameter deviation rate. The anomaly judgment results and equipment status data are fed back to the substation three-dimensional fine design module to provide a basis for updating the three-dimensional model.

[0011] Furthermore, the substation 3D fine design module collects the geometric, physical, and electrical parameters of the substation equipment through multi-source acquisition devices, including laser scanners, high-definition cameras, and sensors. The geometric parameters include at least the length, width, height, and diameter of the equipment; the physical parameters include at least the mass, material, and density of the equipment; and the electrical parameters include at least the rated voltage, rated current, and power of the equipment. The collected equipment parameters are stored in a database to provide data support for the construction of the 3D model.

[0012] Furthermore, the accuracy verification mechanism of the substation three-dimensional fine design module is implemented through an accuracy verification algorithm. The accuracy verification algorithm calculates the average level of the coordinate differences between multiple verification points in the three-dimensional model and the corresponding verification points of the actual equipment to obtain the average error of the model. When the average error of the model meets the preset accuracy requirements, it is determined that the spatial characteristics of the three-dimensional model and the actual equipment are consistent.

[0013] Furthermore, the patrol equipment controlled by the intelligent patrol planning and control module includes drones and robots; the patrol equipment and the intelligent patrol planning and control module transmit data through wireless communication technology, and the patrol equipment obtains its own location information through GPS positioning technology, with a positioning accuracy of ±0.1m.

[0014] Furthermore, when the intelligent patrol planning and control module plans the patrol path based on the 3D model, it adopts an improved A* algorithm. The improved A* algorithm determines the path priority through a comprehensive evaluation function, which integrates at least the actual cost from the starting node to the current node and the estimated cost from the current node to the target node. During the path planning process, the motion characteristics of the patrol equipment are also taken into account, including the maximum speed and turning radius of the equipment, to ensure that the planned path is feasible and safe.

[0015] Furthermore, when the intelligent patrol planning and control module controls the patrol equipment to perform patrol operations, it monitors the working status parameters of the patrol equipment in real time. The working status parameters include at least the battery level, equipment temperature, and sensor working status. When the battery level is detected to be lower than a preset battery level threshold, a low battery alarm is issued and the patrol equipment is controlled to return to base. When the equipment temperature is detected to be higher than a first preset temperature threshold, the operating speed of the patrol equipment is reduced. When the equipment temperature is detected to be higher than a second preset temperature threshold, the patrol equipment is controlled to make an emergency landing, wherein the second preset temperature threshold is higher than the first preset temperature threshold.

[0016] Furthermore, when processing the equipment status data, the data processing and analysis module adopts a combination of data cleaning, filtering, and data normalization. The filtering process is used to correct the current status estimate based on the previous time-to-time state estimate, the current time-to-time control input, and the observed values, so as to reduce the impact of data noise on subsequent analysis.

[0017] Furthermore, when the data processing and analysis module determines that the equipment is abnormal by calculating the feature parameter deviation rate, the feature parameter deviation rate is the degree of deviation between the real-time extracted feature parameter value and the standard value of the feature parameter when the equipment is running normally; when the deviation rate exceeds a preset deviation threshold, it is determined that the equipment is abnormal; and according to the degree to which the deviation rate exceeds the preset threshold, the severity of the abnormality is divided into at least three levels: mild, moderate and severe.

[0018] Furthermore, the anomaly judgment results output by the data processing and analysis module include at least the equipment name, abnormal location, abnormal type, abnormal severity, and suggested handling measures; the output format of the anomaly judgment results includes at least one of text reports, charts, and 3D model annotations; and the anomaly judgment results are stored in the database for the establishment of equipment fault files and subsequent fault analysis.

[0019] Furthermore, when the substation 3D fine design module updates the 3D model based on the equipment change information and the anomaly judgment results output by the data processing and analysis module, if it receives feedback information related to equipment changes, including replacement or modification requirements caused by equipment anomalies, the module automatically retrieves the parameter data of the new equipment from the database, replaces or modifies the corresponding equipment model in the 3D model, and re-verifies the accuracy of the updated model through an accuracy verification mechanism to ensure that the updated 3D model is consistent with the spatial characteristics of the actual equipment.

[0020] Compared with the prior art, the present invention and its preferred embodiments have at least the following beneficial effects:

[0021] By deeply integrating high-precision 3D models with an intelligent inspection system, the core problem of the disconnect between traditional substation design and operation and maintenance is effectively solved. The 3D fine design module adopts multi-source data acquisition and automated accuracy verification mechanisms, keeping the average error of the model within millimeters. This provides a true and reliable digital base map for subsequent inspections, fundamentally avoiding path planning deviations or detection blind spots caused by model distortion.

[0022] The intelligent patrol planning and control module optimizes paths based on 3D models, fully considering the actual motion constraints of the patrol equipment and significantly improving the feasibility and safety of patrol paths. Simultaneously, the system possesses real-time monitoring and intelligent control capabilities for the operating status of the patrol equipment. It can autonomously perform operations such as returning to base, reducing speed, or emergency landing when parameters such as battery power or temperature are abnormal, ensuring the continuity of patrol operations and equipment safety.

[0023] The data processing and analysis module, through multi-level data processing and feature analysis, enables early and accurate diagnosis of equipment anomalies and provides tiered early warnings based on the degree of deviation, offering clear and intuitive basis for operation and maintenance decisions. Crucially, the system constructs a complete closed loop from data acquisition and anomaly diagnosis to model updates, allowing operation and maintenance data to be fed back to the design end in real time, driving dynamic optimization of the 3D model. Ultimately, this achieves seamless and collaborative management of substation data throughout its entire lifecycle, improving the overall intelligence and response efficiency of operation and maintenance.

[0024] This invention forms an integrated design and operation solution through the organic linkage between the above modules. Compared with the independent systems in the prior art, it has significant advantages in terms of data accuracy, operational security and management collaboration. Attached Figure Description

[0025] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0026] Figure 1 This is a system block diagram according to an embodiment of the present invention;

[0027] Figure 2 This is a schematic diagram of the three-dimensional fine design module for substations according to an embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of the intelligent patrol planning and control module according to an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of the data processing and analysis module in an embodiment of the present invention.

[0030] In the diagram: 01. Substation 3D Fine Design Module; 02. Intelligent Inspection Planning and Control Module; 03. Data Processing and Analysis Module; 011. Equipment Parameter Acquisition Unit; 012. 3D Model Construction Unit; 013. Model Accuracy Verification Unit; 014. Model Update Unit; 021. Inspection Requirements Analysis Unit; 022. Path Planning Unit; 023. Inspection Equipment Control Unit; 024. Inspection Process Monitoring Unit; 031. Data Preprocessing Unit; 032. Feature Extraction Unit; 033. Anomaly Diagnosis Unit; 034. Diagnosis Result Output Unit. Detailed Implementation

[0031] In the following, specific embodiments of this application will be described in detail with reference to the accompanying drawings. Based on these detailed descriptions, those skilled in the art will be able to clearly understand and implement this application. Without departing from the principles of this application, features from various embodiments can be combined to obtain new implementations, or certain features from some embodiments can be substituted to obtain other preferred implementations.

[0032] To make the features and advantages of the present invention more apparent and understandable, specific embodiments are described below in conjunction with the accompanying drawings:

[0033] The substation 3D design model and intelligent inspection system provided by this invention includes a substation 3D fine design module, an intelligent inspection planning and control module, and a data processing and analysis module. These modules interact via a data interface. The substation 3D fine design module constructs a high-precision 3D model of the substation. The intelligent inspection planning and control module plans the inspection path of the intelligent inspection equipment and controls the equipment to perform inspection operations. The data processing and analysis module processes and analyzes the inspection data to detect equipment anomalies. This invention constructs a high-precision 3D model of the substation through the substation 3D fine design module, accurately reflecting the detailed features and spatial relationships of the substation equipment. This provides an accurate scene basis for intelligent inspection and avoids inspection errors caused by inaccurate design models.

[0034] Preferably, the substation 3D fine design module includes an equipment parameter acquisition unit, a 3D model construction unit, a model accuracy verification unit, and a model update unit. The equipment parameter acquisition unit uses a laser scanner, high-definition camera, and sensors to acquire the geometric, physical, and electrical parameters of the equipment, with an acquisition accuracy of ±0.1mm. The 3D model construction unit uses AutoCAD Plant 3D or Revit software to construct a 3D model of the substation containing equipment attribute information based on the acquired parameters. The model accuracy verification unit uses an accuracy verification algorithm to verify the model; the calculation formula for the accuracy verification algorithm is... Where E is the average error of the model, n is the number of verification points, Mi is the coordinate value of the i-th verification point in the 3D model, and Ai is the coordinate value of the i-th verification point on the actual device. When E is less than 0.5mm, the model accuracy meets the requirements. The model update unit is used to update the 3D model and re-verify the accuracy when the device changes.

[0035] As a preferred embodiment, the intelligent inspection planning and control module includes an inspection demand analysis unit, a path planning unit, an inspection equipment control unit, and an inspection process monitoring unit. The inspection demand analysis unit determines the inspection object, content, time, and accuracy based on the equipment type, operating status, and maintenance requirements. The path planning unit plans the inspection path based on the substation's 3D model using an improved A* algorithm. The path planning calculation formula is F(n) = G(n) + H(n), where F(n) is the comprehensive evaluation function of node n, G(n) is the actual cost from the starting node to node n, and H(n) is the estimated cost from node n to the target node. The inspection equipment control unit sends control commands to the intelligent inspection equipment and receives feedback data. The inspection process monitoring unit displays the location and trajectory of the inspection equipment in real time, monitors the equipment's operating status, and handles anomalies.

[0036] Preferably, the data processing and analysis module includes a data preprocessing unit, a feature extraction unit, an anomaly diagnosis unit, and a diagnosis result output unit. The data preprocessing unit uses data cleaning, Kalman filtering, and data normalization to process the inspection data. The Kalman filtering state update equation is x^k=Ax^k-1+Buk+Kk(zk-Hx^k-1), where x^k is the state estimate at time k, A is the state transition matrix, x^k-1 is the state estimate at time k-1, B is the control input matrix, uk is the control input at time k, Kk is the Kalman gain, zk is the observation at time k, and H is the observation matrix. The feature extraction unit extracts feature parameters such as equipment appearance, temperature, and vibration. The anomaly diagnosis unit uses machine learning algorithms and anomaly diagnosis formulas to determine equipment anomalies. The diagnosis result output unit outputs the diagnosis results in various forms.

[0037] Preferably, the geometric parameters collected by the equipment parameter acquisition unit include the length, width, height, and diameter of the equipment; the physical parameters include the mass, material, and density of the equipment; and the electrical parameters include the rated voltage, rated current, and power of the equipment. The collected parameter data is stored in a MySQL database.

[0038] As a preferred method, after the 3D model building unit constructs the 3D geometric model of the equipment, it associates the physical and electrical parameters of the equipment with the geometric model, and then combines the substation general layout plan and terrain data to construct a scene model. The equipment model is then placed in the corresponding position of the scene model to form a complete 3D model of the substation.

[0039] Preferably, the intelligent patrol equipment includes a drone and a robot. The drone model is DJI Matrice 350RTK, with a maximum speed of 15 m / s and a turning radius of 2 m. The 4G / 5G wireless communication technology is used to transmit data between the patrol equipment and the control unit, and the position information is located by GPS with an accuracy of ±0.1 m.

[0040] Preferably, the equipment operating status parameters monitored by the patrol process monitoring unit include battery power, equipment temperature, and sensor operating status. When the battery power is lower than 20%, a low-power alarm is issued and the equipment is controlled to return. When the equipment temperature exceeds 50°C, the equipment operating speed is reduced, and when it exceeds 55°C, the equipment is controlled to land urgently.

[0041] Preferably, the abnormal diagnosis formula adopted by the abnormal diagnosis unit is , where D is the deviation rate of the characteristic parameter, F is the value of the characteristic parameter extracted in real time, and F0 is the standard value of the characteristic parameter when the equipment is operating normally. When D is greater than 10%, it is judged that the equipment has an abnormality. According to the size of D, the severity of the abnormality is divided into mild (10% < D ≤ 20%), moderate (20% < D ≤ 30%), and severe (D > 30%).

[0042] Preferably, the diagnosis results output by the diagnosis result output unit include the equipment name, abnormal location, abnormal type, severity, and recommended treatment measures. The output forms include text reports, charts, and three-dimensional model annotations. The diagnosis results are stored in the MySQL database for equipment fault file establishment and subsequent fault analysis.

[0043] Based on the above design, compared with the prior art:

[0044] (1) The present invention constructs a high-precision three-dimensional model of the substation through the three-dimensional fine design module of the substation, which can accurately reflect the detailed features and spatial relationships of the substation equipment, providing an accurate scene basis for intelligent patrol and avoiding patrol errors caused by inaccurate design models.

[0045] (2) The intelligent patrol planning and control module uses an improved A* algorithm for patrol path planning, combines the motion characteristics of the patrol equipment and the requirements of the patrol task, plans a feasible, efficient, and safe patrol path, and simultaneously controls and monitors the operation process of the patrol equipment in real time, improving the patrol efficiency and reliability.

[0046] (3) The data processing and analysis module uses a variety of data processing and machine learning algorithms to process and analyze the patrol data, can timely and accurately detect equipment abnormalities, provide detailed diagnosis results and treatment suggestions for the operation and maintenance personnel, facilitate the operation and maintenance personnel to take measures in time, and ensure the safe and stable operation of the substation.

[0047] (4) This invention realizes the integrated management of substation design and operation and maintenance. The modules interact with each other through data interfaces, so that design data can directly serve operation and maintenance, and operation and maintenance data can also provide reference for design optimization, forming a virtuous cycle of design and operation and maintenance, and improving the overall management level of substation.

[0048] The specific implementation of the present invention will be shown and described in more detail below with reference to the accompanying drawings through three embodiments:

[0049] Example 1

[0050] like Figure 1 , Figure 2 As shown, the substation 3D design model and intelligent inspection system provided in this embodiment include a substation 3D fine design module 01, an intelligent inspection planning and control module 02, and a data processing and analysis module 03. The modules interact with each other through a data interface. The substation 3D fine design module 01 is used to construct a high-precision 3D model of the substation. The intelligent inspection planning and control module 02 is used to plan the inspection path of the intelligent inspection equipment and control the inspection equipment to perform inspection operations. The data processing and analysis module 03 is used to process and analyze the inspection data to detect equipment anomalies.

[0051] As a preferred embodiment, the substation 3D fine design module 01 includes an equipment parameter acquisition unit 011, a 3D model construction unit 012, a model accuracy verification unit 013, and a model update unit 014. The equipment parameter acquisition unit 011 uses a laser scanner, high-definition camera, and sensors to acquire the geometric, physical, and electrical parameters of the equipment, with an acquisition accuracy of ±0.1mm. The 3D model construction unit 012 uses AutoCAD Plant 3D or Revit software to construct a 3D model of the substation containing equipment attribute information based on the acquired parameters. The model accuracy verification unit 013 uses an accuracy verification algorithm to verify the model; the calculation formula for the accuracy verification algorithm is... Where E is the average error of the model, n is the number of verification points, Mi is the coordinate value of the i-th verification point in the 3D model, and Ai is the coordinate value of the i-th verification point on the actual device. When E is less than 0.5mm, the model accuracy meets the requirements. The model update unit 014 is used to update the 3D model and re-verify the accuracy when the device is changed.

[0052] The detailed description of each module in this embodiment is as follows:

[0053] Substation 3D Fine Design Module 01

[0054] This module is used to build a high-precision 3D model of the substation, providing an accurate scene basis for intelligent inspection. It includes an equipment parameter acquisition unit, a 3D model construction unit, a model accuracy verification unit, and a model update unit.

[0055] Equipment parameter acquisition unit 011

[0056] This unit is used to collect geometric, physical, and electrical parameters of various equipment within the substation. Laser scanners, high-definition cameras, and sensors are employed to collect multi-dimensional data from the equipment. Geometric parameters include the equipment's length, width, height, diameter, and other dimensional information, with an acquisition accuracy of ±0.1mm. Physical parameters include the equipment's mass, material, and density. Electrical parameters include the equipment's rated voltage, rated current, and power. The collected parameter data is stored in a database, providing data support for subsequent 3D model construction.

[0057] 3D Model Building Unit 012

[0058] Based on the data collected by the equipment parameter acquisition unit, a 3D model of the substation is constructed using 3D modeling software (such as AutoCAD Plant 3D, Revit, etc.). First, a 3D geometric model of the equipment is established according to its geometric parameters, ensuring that the model's shape matches the actual equipment. Then, the physical and electrical parameters of the equipment are associated with the 3D geometric model, so that the model not only has a geometric shape but also contains the equipment's attribute information. For the substation scene model, based on the substation's general layout plan and terrain data, 3D models of scene elements such as substation buildings, roads, and green spaces are constructed, and the equipment models are placed in their corresponding scene locations to form a complete 3D model of the substation.

[0059] Model accuracy verification unit 013

[0060] To ensure the accuracy of the constructed 3D model, this unit employs an accuracy verification algorithm to validate the model. The calculation formula for the accuracy verification algorithm is as follows: Where E is the average error of the model, n is the number of verification points, Mi is the coordinate value of the i-th verification point in the 3D model, and Ai is the coordinate value of the i-th verification point on the actual device. When the calculated average error E is less than the set error threshold (e.g., 0.5 mm), the model accuracy is considered to meet the requirements; otherwise, the model is returned to the 3D model building unit for correction until the model accuracy meets the requirements.

[0061] Model update unit 014

[0062] With the replacement, renovation, or expansion of substation equipment, timely updates to the 3D model are necessary. This unit monitors equipment change information at the substation. Upon receiving a change instruction, it automatically retrieves the parameter data of the new equipment from the database, replaces or modifies the corresponding equipment model in the 3D model, and updates the model's attribute information. Simultaneously, it performs accuracy verification on the updated model to ensure that its accuracy still meets requirements, guaranteeing consistency between the 3D model and the actual substation conditions.

[0063] The equipment parameter acquisition unit 011 collects geometric parameters including the length, width, height, and diameter of the equipment; physical parameters including the mass, material, and density of the equipment; and electrical parameters including the rated voltage, rated current, and power of the equipment. The collected parameter data is stored in a MySQL database.

[0064] After the 3D model building unit 012 builds the 3D geometric model of the equipment, it associates the physical and electrical parameters of the equipment with the geometric model, and then combines the substation general layout plan and terrain data to build a scene model. The equipment model is then placed in the corresponding position of the scene model to form a complete 3D model of the substation.

[0065] As a preferred embodiment, the intelligent patrol equipment includes a drone and a robot. The drone model is DJI Motrice 350 RTK, with a maximum speed of 15 m / s and a turning radius of 2 m. The patrol equipment and the control unit transmit data using 4G / 5G wireless communication technology, and the location information is obtained using GPS positioning with an accuracy of ±0.1 m.

[0066] Example 2

[0067] Based on Example 1, such as Figure 3 As shown, the intelligent inspection planning and control module 02 includes an inspection demand analysis unit 021, a path planning unit 022, an inspection equipment control unit 023, and an inspection process monitoring unit 024. The inspection demand analysis unit 021 determines the inspection object, content, time, and accuracy based on the equipment type, operating status, and maintenance requirements. The path planning unit 022 plans the inspection path based on the substation's three-dimensional model using an improved A* algorithm. The path planning calculation formula is F(n) = G(n) + H(n), where F(n) is the comprehensive evaluation function of node n, G(n) is the actual cost from the starting node to node n, and H(n) is the estimated cost from node n to the target node. The inspection equipment control unit 023 sends control commands to the intelligent inspection equipment and receives feedback data. The inspection process monitoring unit 024 displays the location and trajectory of the inspection equipment in real time, monitors the equipment's working status, and handles anomalies.

[0068] The detailed description of each module in this embodiment is as follows:

[0069] Intelligent Inspection Planning and Control Module 02

[0070] This module is used to plan the patrol path of intelligent patrol equipment and control the patrol equipment to carry out patrol operations according to the planned path. It includes a patrol demand analysis unit, a path planning unit, a patrol equipment control unit, and a patrol process monitoring unit.

[0071] Inspection Needs Analysis Unit 021

[0072] This unit analyzes and determines inspection needs based on the equipment type, operating status, importance, and maintenance requirements of the substation. First, the equipment within the substation is categorized, such as transformers, circuit breakers, and disconnectors. Then, the importance and inspection cycle of the equipment are determined based on its service life, historical fault records, and load conditions. Finally, in conjunction with the substation's maintenance plan, specific inspection tasks are formulated, clarifying the inspection targets, content, time, and accuracy requirements for each task.

[0073] Path planning unit 022

[0074] Based on a 3D model constructed using a substation 3D fine-design module, an improved A* algorithm is employed for inspection path planning. The improved A* algorithm, building upon the traditional A* algorithm, considers factors such as the motion characteristics of the inspection equipment (e.g., turning radius, maximum speed), the safe distance between equipment, and the priority of inspection tasks to ensure the planned path is feasible, efficient, and safe. The goal of path planning is to minimize the travel distance and inspection time of the inspection equipment while meeting the requirements of the inspection task. The calculation formula for path planning is as follows: F(n) = G(n) + H(n), where F(n) is the comprehensive evaluation function of node n, G(n) is the actual cost (e.g., travel distance, time) from the starting node to node n, and H(n) is the estimated cost (calculated using methods such as Manhattan distance and Euclidean distance) from node n to the target node. By continuously calculating the F(n) value of each node, the node with the smallest F(n) value is selected as the next node to be expanded, until the optimal inspection path from the starting node to the target node is found.

[0075] Inspection equipment control unit 023

[0076] This unit sends control commands to intelligent inspection equipment (such as drones and robots) based on the inspection path planned by the path planning unit, controlling the inspection equipment to perform inspection operations according to the planned path. Control commands include actions such as starting, stopping, turning, accelerating, and decelerating the equipment, as well as operating commands for the sensors on the equipment (such as cameras, infrared thermal imagers, and ultrasonic sensors). Simultaneously, this unit receives real-time position information, attitude information, and sensor data from the inspection equipment, adjusting the control commands based on the feedback to ensure the inspection equipment accurately follows the planned path and completes the inspection data collection task.

[0077] Inspection process monitoring unit 024

[0078] During the inspection of the equipment, this unit monitors the progress of the inspection in real time. The location and trajectory of the inspected equipment are displayed in real time using a 3D model of the substation, allowing maintenance personnel to intuitively understand the inspection progress. Simultaneously, it monitors the operating status of the inspected equipment, such as battery level, equipment temperature, and sensor functionality. When an abnormality is detected (e.g., low battery or equipment malfunction), an alarm signal is promptly issued, and appropriate measures are taken based on the situation, such as controlling the equipment to return to charging or dispatching maintenance personnel for repairs, ensuring the successful completion of the inspection mission.

[0079] The monitoring unit 024 monitors the equipment's operating status parameters, including battery level, equipment temperature, and sensor operating status. When the battery level is below 20%, it issues a low battery alarm and controls the equipment to return to base. When the equipment temperature exceeds 50°C, it reduces the equipment's operating speed. When the temperature exceeds 55°C, it controls the equipment to make an emergency landing.

[0080] Example 3

[0081] Based on Example 2, such as Figure 4 As shown, the data processing and analysis module 03 includes a data preprocessing unit 031, a feature extraction unit 032, an anomaly diagnosis unit 033, and a diagnosis result output unit 034. The data preprocessing unit 031 processes the inspection data using data cleaning, Kalman filtering, and data normalization. The Kalman filtering state update equation is x^k=Ax^k-1+Buk+Kk(zk-Hx^k-1), where x^k is the state estimate at time k, A is the state transition matrix, x^k-1 is the state estimate at time k-1, B is the control input matrix, uk is the control input at time k, Kk is the Kalman gain, zk is the observation at time k, and H is the observation matrix. The feature extraction unit 032 extracts feature parameters such as equipment appearance, temperature, and vibration. The anomaly diagnosis unit 033 uses machine learning algorithms (such as SVM and neural networks) and anomaly diagnosis formulas to determine equipment anomalies. The diagnosis result output unit 034 outputs the diagnosis results in various forms.

[0082] The abnormal diagnosis formula adopted by the abnormal diagnosis unit 033 is , where D is the deviation rate of the characteristic parameter, F is the value of the characteristic parameter extracted in real time, and F0 is the standard value of the characteristic parameter when the device is operating normally. When D is greater than 10%, it is determined that the device has an abnormality. According to the magnitude of D, the severity of the abnormality is divided into mild (10% < D ≤ 20%), moderate (20% < D ≤ 30%), and severe (D > 30%).

[0083] The diagnosis result output unit 034 outputs the diagnosis result including the device name, abnormal location, abnormal type, severity, and recommended handling measures. The output forms include text reports, charts, and three-dimensional model annotations. The diagnosis results are stored in the MySQL database for establishing the device fault file and subsequent fault analysis.

[0084] Meanwhile, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0085] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0086] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0087] These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured product including instruction means, and the instruction means implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0088] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0089] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0090] The foregoing has shown and described the basic principles, main features, and advantages of this disclosure. Those skilled in the art should understand that this disclosure is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of this disclosure. Various changes and modifications can be made to this disclosure without departing from its spirit and scope, and all such changes and modifications fall within the scope of this disclosure as claimed.

[0091] This invention is not limited to the preferred embodiment described above. Anyone inspired by this invention can derive various other forms of three-dimensional design models and intelligent inspection systems for substations. All equivalent variations and modifications made within the scope of the patent applications of this invention shall fall within the scope of this invention.

Claims

1. A substation three-dimensional design model and intelligent patrol system, characterized in that, The application relates to a substation three-dimensional fine design module, an intelligent patrol planning and control module and a data processing and analysis module which realize data interaction through a data interface. The substation three-dimensional fine design module is used for constructing a three-dimensional model of a substation, ensuring that the three-dimensional model and the spatial features of actual equipment are less than a preset threshold value through a precision checking mechanism, the spatial features including the geometric size, relative position and topological relationship of the equipment, and updating the three-dimensional model based on equipment change information and the abnormal judgment result output by the data processing and analysis module. The intelligent patrol planning and control module is used for planning a patrol path of a patrol device based on the three-dimensional model and controlling the patrol device to perform a patrol operation to collect equipment state data. The data processing and analysis module is used for processing the equipment state data, extracting equipment characteristic parameters and judging equipment abnormalities through a characteristic parameter deviation rate, and feeding back the abnormal judgment result and the equipment state data to the substation three-dimensional fine design module to provide a basis for updating the three-dimensional model. The substation three-dimensional fine design module collects geometric parameters, physical parameters and electrical parameters of substation equipment through multi-source collection equipment, the multi-source collection equipment including a laser scanner, a high-definition camera and a sensor, the geometric parameters at least including the length, width, height and diameter of the equipment, the physical parameters at least including the mass, material and density of the equipment, and the electrical parameters at least including the rated voltage, rated current and power of the equipment; the collected equipment parameters are stored in a database to provide data support for the construction of the three-dimensional model.

2. The substation 3D design model and intelligent patrol system of claim 1, wherein: The precision checking mechanism of the substation three-dimensional fine design module is realized through a precision checking algorithm, the precision checking algorithm obtains a model average error by calculating the average level of the coordinate difference between a plurality of checking points in the three-dimensional model and corresponding checking points of actual equipment; when the model average error meets the preset precision requirement, it is determined that the three-dimensional model is consistent with the spatial features of the actual equipment.

3. The substation 3D design model and intelligent patrol system of claim 1, wherein: The patrol device controlled by the intelligent patrol planning and control module includes a drone and a robot; the patrol device and the intelligent patrol planning and control module transmit data through wireless communication technology, and the patrol device obtains its own position information through GPS positioning technology, and the positioning accuracy is + / -0.1m.

4. The substation 3D design model and intelligent patrol system of claim 1, wherein: When the intelligent patrol planning and control module plans a patrol path based on the three-dimensional model, an improved A* algorithm is adopted; the improved A* algorithm determines the path priority through a comprehensive evaluation function, the comprehensive evaluation function at least fusing the actual cost from a starting node to a current node and the estimated cost from the current node to a target node; 5. The substation 3D design model and intelligent patrol system of claim 1, wherein: During the planning path process, the motion characteristics of the patrol device, including the maximum speed and turning radius of the equipment, are combined to ensure that the planned path is feasible and safe. ​ 6. The substation 3D design model and intelligent patrol system of claim 1, wherein: The intelligent patrol planning and control module monitors the working state parameters of the patrol device in real time when controlling the patrol device to perform the patrol task, and the working state parameters at least include battery power, device temperature and sensor working state; when monitoring that the battery power is lower than the preset power threshold, a low power alarm is sent and the patrol device is controlled to return; when monitoring that the device temperature exceeds the first preset temperature threshold, the running speed of the patrol device is reduced; when monitoring that the device temperature exceeds the second preset temperature threshold, the patrol device is controlled to land urgently, wherein the second preset temperature threshold is higher than the first preset temperature threshold.

7. The substation 3D design model and intelligent patrol system of claim 1, wherein: When the data processing and analysis module processes the device state data, a combination processing mode of data cleaning, filtering processing and data normalization is adopted; wherein the filtering processing is used to correct the state estimation value at the current moment based on the state estimation value at the previous moment, the control input and the observation value at the current moment, so as to reduce the influence of data noise on subsequent analysis.

8. The substation 3D design model and intelligent patrol system of claim 1, wherein: When the data processing and analysis module determines the device abnormality through the feature parameter deviation rate, the feature parameter deviation rate is the deviation degree between the real-time extracted feature parameter value and the feature parameter standard value when the device is normally running; when the deviation rate exceeds the preset deviation threshold, it is determined that the device has an abnormality; and according to the degree that the deviation rate exceeds the preset threshold, the abnormality severity is divided into at least three levels of mild, moderate and severe.

9. The substation 3D design model and intelligent patrol system of claim 1, wherein: The abnormality judgment result output by the data processing and analysis module at least includes device name, abnormal position, abnormal type, abnormal severity and suggested treatment measures; the output form of the abnormality judgment result includes at least one of a text report, a chart and a three-dimensional model annotation; and the abnormality judgment result is stored in a database for establishing a device fault file and subsequent fault analysis.

10. The substation 3D design model and intelligent patrol system of claim 1, wherein: When the transformer substation three-dimensional fine design module updates the three-dimensional model based on the device change information and the abnormality judgment result output by the data processing and analysis module, when receiving feedback information related to device change, the feedback information related to device change includes replacement and modification requirements caused by device abnormality, the module automatically retrieves parameter data of new devices from the database, replaces or modifies corresponding device models in the three-dimensional model, and rechecks the accuracy of the updated model through the accuracy checking mechanism to ensure that the updated three-dimensional model is consistent with the spatial characteristics of the actual device.

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