A control method and control system of a high-voltage substation pipe busbar dismounting robot

Abstract

The application discloses a high-voltage transformer substation pipe mother drainage line dismounting robot control method and a control system, and relates to the technical field of electric power construction. The method comprises data collection: obtaining a high-voltage transformer substation basic data set, an AR device data set, a robot data set, a fault data set and a maintenance criterion data set, wherein the fault data set comprises a real-time fault data set and a historical fault data set, and the high-voltage transformer substation basic data set comprises a drainage line information data set. Through a quick connection method, the AR device can quickly establish a control relationship with a specified dismounting robot, the time for searching and pairing devices in the traditional method is reduced, the operation efficiency is improved, the introduction of a command set and a self-defined command mode enables an operator to quickly create and modify commands on an intuitive operation interface by using the AR device, the convenience and flexibility of operation are greatly enhanced, and the operator can adjust the commands in real time according to the on-site situation to adapt to a complex and changeable operation environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power construction, in particular to a high-voltage substation pipe busbar drainage line dismounting robot control method and control system. BACKGROUND

[0002] With the continuous development of the power system, the safety and reliability of high-voltage substations, which are key links in power transmission and distribution, are increasingly valued. In high-voltage substations, the dismounting operation of pipe busbar drainage lines is a common maintenance task, but this operation process often faces many challenges, such as complex operating environment, high safety risks, and low efficiency of traditional manual operation. Traditionally, the dismounting operation of pipe busbar drainage lines in high-voltage substations relies on manual operation, which is not only inefficient but also has high safety risks.

[0003] For example, patent CN116394243A entitled "Robot control system, method, device and robot" discloses a robot control system including a management platform and multiple robots. The management platform determines a specified formation of the multiple target robots and issues the specified formation. Each target robot adjusts its position according to the specified formation. Each slave robot detects the initial detection position of the master robot and reports a first notification message when the detection error between the detected detection position relationship and the specified position relationship meets the detection error condition. The master robot determines an initial formation and reports a second notification message when the positioning error between the initial formation and the specified formation meets the positioning error condition and the first notification message reported by each slave robot is received. The management platform issues a task start instruction based on the second notification message. Each target robot executes the to-be-executed task, and multiple robots can be controlled to work cooperatively.

[0004] The above technology focuses on the formation control between robots and the synchronization of task start, which may not be suitable for the complex and variable operating environment of high-voltage substations. Existing dismounting robots require operators to use matching controllers to perform dismounting operations on high-altitude drainage lines. However, the drainage lines cannot be dismounted by simply pulling them, and the fault drainage lines need to be surveyed to obtain information such as specifications, fixtures, and fault conditions, so that the dismounting robot can perform precise dismounting operations. However, this step still requires manual recording and analysis of the above information by the operator, making it more cumbersome to operate the dismounting robot and increasing the risk of accidents during the operation process. SUMMARY

[0005] The present application aims to provide a high-voltage substation pipe busbar drainage line dismounting robot control method and control system to solve the problems raised in the background.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] The first aspect designs a control method of a high-voltage substation pipe busbar disassembly robot, the control method comprises:

[0008] Data collection: obtain a high-voltage substation basic data set, an AR device data set, a robot data set, a fault data set, and a maintenance criterion data set, the fault data set includes a real-time fault data set and a historical fault data set, and the high-voltage substation basic data set includes a busbar information data set;

[0009] Server building: build a cloud server, a database is arranged in the cloud server to store the high-voltage substation basic data set, the AR device data set, the robot data set, the fault data set, and the maintenance criterion data set, a geographic space of the high-voltage substation is arranged in the cloud server, and a feature database is established based on the fault data set;

[0010] Order distribution: the cloud server creates a maintenance order after obtaining the real-time fault data set, and the maintenance order is distributed to the AR device according to an order distribution method;

[0011] On-site survey analysis: an operator wears an AR device to control a disassembly robot to conduct on-site surveying according to a device control method, the disassembly robot is integrated with a surveying device for obtaining surveying information and uploading the surveying information to the cloud server, the cloud server generates a maintenance report based on the surveying information and sends the maintenance report to the AR device;

[0012] The operator uses the AR device and controls the disassembly robot again according to the device control method based on the maintenance report to perform maintenance work;

[0013] The device control method comprises:

[0014] S1: Establish a connection, each disassembly robot is provided with an independent controller, and the AR device is quickly connected to the corresponding controller through a quick connection method;

[0015] S2: Control command, the operator uses the AR device to create a command set for controlling a specified disassembly robot to execute work in a fixed order, and the command set is stored in the AR device;

[0016] S3: Release the device, the AR device sends an end command to the controller on the specified disassembly robot based on the command set, and after receiving the end command, the specified disassembly robot moves to a specified position according to a device movement method.

[0017] Further, the quick connection method comprises:

[0018] A1: The cloud server obtains device state set based on the robot data set, and sends the device state set to the AR device;

[0019] A2: Based on the maintenance order, the operator selects the disassembly / assembly robot that best matches the current location information and current status information from the equipment status set and sends a control request;

[0020] A3: After the cloud service accepts the control request, it establishes a temporary control relationship between the designated assembly / disassembly robot and the AR device.

[0021] Furthermore, the method for creating the command set includes:

[0022] B1: The operator uses the AR device to create a command framework based on the AR device dataset. The command framework is filled with basic operation methods and custom command methods. Both the basic operation methods and custom command methods are set in multiple ways and are matched one by one with different types of disassembly and assembly robots.

[0023] B2: Operators can add their own required commands using the AR device's custom command method to obtain the executable command set for different assembly and disassembly robots;

[0024] B3: Operators use AR devices to add command operation rules, allowing basic operation methods, custom command methods, and executable command sets to run within the rules.

[0025] Furthermore, the device relocation method includes:

[0026] C1: The cloud server uses GIS technology to establish the geospatial data of the high-voltage substation based on the basic dataset of the high-voltage substation. Multiple machine storage points are set up in the geospatial data, and each machine storage point is used to store a dedicated disassembly and assembly robot.

[0027] C2: The cloud server obtains the current coordinate information of the released disassembly and assembly robot, and obtains the corresponding machine storage point coordinate information, thereby obtaining the target coordinate information set;

[0028] C3: The cloud server uses a pathfinding algorithm based on geospatial information to find and generate the best movement path. The released disassembly and assembly robots then move to the corresponding machine storage point according to the best movement path.

[0029] Furthermore, the order delivery method includes:

[0030] T1: The cloud server uses the AR device dataset to count the current status of each AR device, counts the number of currently executed repair orders based on the current status of each AR device, and counts the estimated completion time of each repair order based on the current number of repair orders, thereby obtaining the current AR device status set;

[0031] T2: Calculate the distance between the repair site and each AR device based on the current AR device status set and repair orders, and calculate the arrival time. Then, calculate the sum of the estimated completion times of all repair orders in each AR device and add the arrival time. After sorting, select the AR device with the time closest to the current time as the target AR device for order delivery.

[0032] T3: The cloud server sends the repair order to the target AR device via a private local area network.

[0033] Furthermore, the method for creating the feature database is as follows:

[0034] N1: Standard data is obtained by preprocessing and integrating the drainage line information dataset and the fault dataset;

[0035] N2: Based on standard data, features are extracted using image processing techniques, and the features are classified and labeled to establish a feature subset. The features include the shape, color, and fault condition of the drainage line.

[0036] N3: Establish database tables based on standard data and feature subsets, and define the database tables, which include a fault feature table, a fault type table, and a maintenance criterion table;

[0037] N4: Based on the database tables, standard data and feature subsets are updated to the corresponding database tables in real time, thereby obtaining the feature database.

[0038] Furthermore, the method for generating the maintenance report includes:

[0039] Y1: Based on the survey information, key features are extracted using image processing technology, and sensor data from the survey information set are integrated to obtain the survey information set;

[0040] Y2: Based on key features and feature database, corresponding features are obtained by matching, and then corresponding fault types are obtained based on the corresponding features and combined with sensor data to obtain an evaluation report;

[0041] Y3: The maintenance report is obtained based on the assessment report, maintenance criteria dataset, and survey information set.

[0042] Furthermore, the AR device establishes a connection with the controller via a temporarily created private local area network (PLAN) for information transmission. The method for creating the PLAN includes:

[0043] M1: The cloud server identifies the AR device ID and the assembly / disassembly robot ID based on the control request, and then automatically allocates a temporary communication channel to match the IP of the AR device with the corresponding IP of the assembly / disassembly robot;

[0044] M2: Cloud servers configure network services and security measures for temporary communication channels;

[0045] M3: After the AR device issues the end command, the cloud server receives the command and automatically cancels the temporary communication channel, as well as the corresponding logistics network services and security measures.

[0046] Furthermore, the surveying equipment includes an infrared thermal imager, a high-definition camera, a laser rangefinder, and an electromagnetic field detector.

[0047] Secondly, based on the above-mentioned control method for dismantling and assembling a robot for a high-voltage substation busbar, a control system for a robot for dismantling and assembling a high-voltage substation busbar was designed.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] A control method and control system for a high-voltage substation busbar disconnection and assembly robot are disclosed. Through a rapid connection method, AR devices can quickly establish a control relationship with designated disconnection and assembly robots, reducing the time spent searching for and pairing devices in traditional methods and improving operational efficiency. The introduction of command sets and custom command methods allows operators to quickly create and modify commands on an intuitive operating interface using AR devices, greatly enhancing operational convenience and flexibility. Operators can adjust commands in real time according to site conditions to adapt to complex and changing operating environments. The equipment movement method, through GIS technology and pathfinding algorithms, plans the optimal movement path for the disconnection and assembly robot, ensuring that the robot can quickly and safely return to the storage point after completing its task, avoiding resource idleness and waste. The entire control method emphasizes real-time monitoring and precise control of the disconnection and assembly robot's status. Through feedback from the equipment status set and precise execution of the command set, it reduces safety risks caused by improper operation or equipment failure.

[0050] Meanwhile, the order dispatch method quickly selects the most suitable AR device as the order delivery target based on the status of the AR device, the estimated completion time of the repair order, and the distance of the AR device to the repair site, improving the efficiency of order dispatch and ensuring the timeliness of fault repair. On-site surveys can obtain accurate survey information in real time and generate detailed repair reports, providing a scientific basis for subsequent repair work and ensuring the pertinence and effectiveness of the repair work. The feature database integrates standard data through preprocessing and extracts key features using image processing technology, enabling more accurate matching of corresponding features during subsequent fault identification. The repair report uses these classified and labeled feature subsets to match with real-time survey information, which can quickly locate the fault type, reduce the possibility of misjudgment and omission, and improve the accuracy and efficiency of fault identification. Attached Figure Description

[0051] Figure 1 This is a schematic diagram illustrating the principle of the present invention;

[0052] Figure 2 This is a schematic diagram illustrating the principle of the device control method of the present invention;

[0053] Figure 3 This is a schematic diagram illustrating the principle of the repair report of the present invention;

[0054] Figure 4 This is a schematic diagram of the high-voltage substation of the present invention. Detailed Implementation

[0055] 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. 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.

[0056] In the daily operation and maintenance of high-voltage substations, this invention provides a control method and control system for a robot to dismantle and install busbar leads in high-voltage substations. This method is suitable for complex substation environments that require efficient and precise handling of busbar dismantling and installation operations and rapid fault response. It enables remote control and on-site analysis through AR equipment, greatly improving work efficiency and safety. Operators need to have professional skills and be familiar with the AR equipment's operating interface and the robot's control process. During operation, operators need to wear AR equipment, receive maintenance orders based on real-time fault data, and use AR equipment to control the robot for on-site surveying and maintenance. At the same time, they must strictly abide by safety operating procedures to ensure personal safety and stable equipment operation during the operation.

[0057] like Figures 1-4 As shown, the present invention provides a technical solution: a control method for a robot to disconnect and connect a high-voltage substation busbar, the control method comprising:

[0058] Data collection: Acquire basic datasets for high-voltage substations, AR equipment datasets, robot datasets, fault datasets, and maintenance guideline datasets. The fault datasets include real-time fault datasets and historical fault datasets. The basic datasets for high-voltage substations include a feed line information dataset.

[0059] It is important to note the following datasets: High-voltage substation basic dataset: substation geographic data / substation layout map / equipment specifications and models / operating parameters / safety regulations and standards; AR equipment dataset: equipment models and specifications / performance evaluation data / maintenance and fault records; Robot dataset: robot models and configurations / task execution data / environmental adaptability data / path planning and navigation data / maintenance and fault logs / survey equipment models; Fault dataset: fault types and descriptions / fault cause analysis / handling measures and results / fault impact assessment / historical fault cases; Maintenance guideline dataset: maintenance standards and procedures / maintenance tools and materials / safety regulations / maintenance record templates / maintenance training and assessment; Drainage wire information dataset: drainage wire identifier / type / specification / length / electrical characteristics / insulation class / withstand voltage level / mechanical strength parameters / starting and ending connection points / connection method / specification and quantity of connecting fasteners.

[0060] Server setup: Set up a cloud server with a database to store basic datasets for high-voltage substations, AR equipment datasets, robot datasets, fault datasets, and maintenance guidelines datasets. The cloud server also contains the geospatial data of the high-voltage substations and establishes a feature database based on the fault datasets.

[0061] It is important to note that you need to select a cloud service platform (AWS, Azure, Alibaba Cloud, and Tencent Cloud), choose the appropriate cloud server instance type according to your needs, configure network settings, start the cloud server instance, and obtain its IP address and login credentials. Connect to your cloud server via SSH or remote desktop, install the necessary service software, select a suitable MySQL database system, install and configure the database system, create databases and users, and set access permissions. Import the high-voltage substation basic dataset, AR equipment dataset, robot dataset, fault dataset, and maintenance guideline dataset into the database. Use GIS technology to transform the substation geographic data into geospatial data and integrate map APIs for display. Finally, establish a feature database.

[0062] Order dispatch: After obtaining the real-time fault dataset, the cloud server creates a repair order, which is then dispatched to the AR device according to the order dispatch method.

[0063] On-site survey and analysis: Operators wearing AR devices control the disassembly and assembly robot to conduct on-site surveys using the equipment operation method. The disassembly and assembly robot is equipped with survey equipment to acquire survey information and upload it to the cloud server. The cloud server generates a maintenance report based on the survey information and sends it to the AR device.

[0064] The operator uses AR equipment and, based on the maintenance report, manipulates the disassembly and assembly robot to perform maintenance work according to the equipment operation method.

[0065] likeFigure 2 As shown, the equipment control method includes: S1: Establishing a connection. Each assembly / disassembly robot is equipped with an independent controller. The AR device quickly connects to the corresponding controller through a quick connection method. S2: Control commands. The operator uses the AR device to create a command set to control the designated assembly / disassembly robot to perform work in a fixed sequence. The command set is stored on the AR device. S3: Releasing the equipment. The AR device sends an end command to the controller on the designated assembly / disassembly robot based on the command set. After receiving the end command, the designated assembly / disassembly robot moves to the designated position according to the equipment movement method.

[0066] It is important to note that each assembly / disassembly robot is equipped with an independent controller. This controller has a wireless communication module for communicating with the AR device. The controller also needs an actuator control interface to receive and execute commands from the AR device. The robot has a positioning and navigation system to autonomously move to a designated location when needed. The AR device must have wireless communication capabilities compatible with the assembly / disassembly robot's controller. The device should have dedicated control software installed, allowing the operator to create and send command sets via gestures, voice, or interface buttons. The AR device should also have a display function to show the operator real-time visuals and robot status information. The operator activates the AR device and its control software to establish a wireless connection with the assembly / disassembly robot's controller using a quick connection method. After the connection is established, the operator can communicate via the AR device... Command sets are created via interface or voice commands. Each command set contains a series of specific instructions used to control a designated assembly / disassembly robot to perform a specific workflow. Once the command set is created, the robot's controller receives the command set from the AR device, parses the instructions, and executes the corresponding actions. During the robot's execution, its status information can be fed back to the AR device in real time and displayed to the operator on the AR device's screen. If an abnormal situation is encountered during execution, the robot will pause execution and send an alarm message to the AR device. When the assembly / disassembly robot completes the designated task, the operator issues a termination command on the AR device. The AR device sends the termination command to the robot's controller. Upon receiving the termination command, the controller stops the robot's current action and moves it to the designated machine storage point according to the device movement method.

[0067] like Figure 2 As shown, the quick connection method includes: A1: The cloud server obtains the current location information and current status information of the disassembly and assembly robot based on the robot dataset to obtain the device status set, and sends the device status set to the AR device; A2: The operator selects the disassembly and assembly robot whose current location information and current status information best match the device status set based on the maintenance order and sends a control request; A3: After the cloud service accepts the control request, it establishes a temporary control relationship between the specified disassembly and assembly robot and the AR device.

[0068] It's important to note that the assembly / disassembly robot periodically uploads its location and status information to the cloud server for updates. The cloud server processes this information, generates a device status set, and stores it for future reference. Operators access this data on the cloud server via AR devices, typically through an application on the AR device. This application establishes a network connection with the cloud server. Operators view maintenance orders, understand the tasks to be performed, and the required robot type or specific conditions. Operators browse the device status set on the AR device and, based on the maintenance order requirements, select the assembly / disassembly robot whose current location and status information best match the set. Once a suitable robot is selected, the AR device generates a control request. This request includes the selected robot's unique identifier (such as an ID number) and an overview of the instructions or command set the operator wishes to execute. The AR device sends the control request to the cloud server. Upon receiving the control request, the cloud server first verifies its validity. If the verification is successful, the cloud server forwards the control request to the designated assembly / disassembly robot. Meanwhile, the cloud server updates records in the database, establishing a temporary control relationship between the assembly / disassembly robot and the AR device. After receiving a control request from the cloud server, the assembly / disassembly robot parses the request content and confirms whether it is ready to accept control. If the robot is ready, it will establish a direct wireless communication connection with the AR device through its controller. After the communication connection is established, the robot enters a standby state, waiting to receive specific instructions from the AR device. The AR device sends specific instructions or command sets to the assembly / disassembly robot through the established communication connection. The assembly / disassembly robot receives the instructions and executes the corresponding operations. During the execution, the robot feeds back real-time status information (such as progress, anomalies, etc.) to the AR device so that the operator can monitor and adjust. When the assembly / disassembly robot completes the designated task, it sends a task completion notification to the AR device. After the operator confirms that the task is completed, it initiates a disconnection request on the AR device. After receiving the disconnection request, the cloud server and the assembly / disassembly robot respectively execute the corresponding operations to end the temporary control relationship and release the relevant resources.

[0069] like Figure 2 As shown, the method for creating a command set includes: B1: The operator creates a command framework using the AR device based on the AR device dataset. The command framework is filled with basic operation methods and custom command methods. Both basic operation methods and custom command methods have multiple options and are matched one by one with different types of disassembly and assembly robots. B2: The operator adds required commands using the custom command methods of the AR device to obtain the executable command set for different disassembly and assembly robots. B3: The operator adds command operation rules using the AR device to ensure that the basic operation methods, custom command methods, and executable command sets operate within the rules.

[0070] It's important to note that the AR device dataset contains information such as operating specifications and capability ranges for different types of assembly / disassembly robots. Operators launch a command set creation tool on the AR device. This tool provides a visual interface for designing command frameworks. The interface may contain multiple configurable blocks to distinguish between basic operation methods (such as movement, rotation, and grasping) and custom command methods (commands designed according to specific needs). Within the command framework, each basic operation method and custom command method needs to be matched one-to-one with a specific type of assembly / disassembly robot. This is typically achieved through drop-down menus, selection boxes, or conditional statements, allowing operators to select different command options for different types of robots. Based on the command framework, the AR device provides a custom command editing interface. This interface allows operators to input new command names, descriptions, parameters, etc. Operators analyze which additional commands are needed to support the operation based on the current maintenance task or the specific requirements of the assembly / disassembly robot. Through the custom command interface, operators input these new commands and associate them with the corresponding assembly / disassembly robot type. Custom commands may need to be associated with the assembly / disassembly robot's API. To ensure correct execution, the AR device is compatible with the I or control protocol. After adding custom commands, the operator needs to verify that these commands meet expectations and test their execution effect on the assembly / disassembly robot. The AR device provides a rule editor that allows the operator to add operation rules to the command set. These rules can define the logical relationships between commands, execution order, condition judgments, etc. The operator sets rules in the rule editor, such as specifying that certain commands must be executed after other commands, or enabling or disabling certain commands based on the current state of the assembly / disassembly robot. After the settings are completed, these rules will be automatically applied to the command set to ensure that all commands run within the specified range. When the operator sends commands to the assembly / disassembly robot through the AR device, the system will filter and adjust the commands according to these rules. After completing the creation of the command framework, the addition of custom commands, and the setting of command operation rules, the AR device integrates all these elements into a complete executable command set. The command set is deployed to a cloud server or directly transmitted to the assembly / disassembly robot to ensure that the operator can access and use these commands at any time when performing tasks. With the advancement of assembly / disassembly robot technology and changes in task requirements, the operator may need to update and maintain the command set regularly to ensure that it remains effective and efficient.

[0071] like Figure 2As shown, the equipment relocation method includes: C1: The cloud server uses GIS technology to establish the geospatial data of the high-voltage substation based on the high-voltage substation basic dataset. Multiple machine storage points are set in the geospatial data, and each machine storage point is used to store a dedicated dismantling and assembly robot. C2: The cloud server obtains the current coordinate information of the released dismantling and assembly robot and obtains the coordinate information of the corresponding machine storage point, thereby obtaining the target coordinate information set. C3: The cloud server uses a pathfinding algorithm to find and generate the best movement path based on the geospatial data. The released dismantling and assembly robot moves to the corresponding machine storage point according to the best movement path.

[0072] It is important to note that the cloud server first collects basic datasets of the high-voltage substation, including substation floor plans, building structures, equipment layouts, and safety zone delineation. Using Geographic Information System (GIS) technology, this basic data is converted into a digital map, constructing a 3D or 2D geographic space containing detailed geographic information of the high-voltage substation. Within this geographic space, multiple machine storage points are set up according to the substation layout and the needs of the assembly / disassembly robots. Each storage point should have sufficient space to house its dedicated assembly / disassembly robot. Considering safety, maintenance, and ease of operation, the location information of the machine storage points (such as latitude, longitude, and coordinates) is stored in the cloud server's database for later retrieval and use. When the assembly / disassembly robot completes its task and is released, it sends its current coordinates to the cloud server via its built-in GPS system or other positioning device. The cloud server, based on the robot's model, status, or task requirements, queries the database for the corresponding machine storage point coordinates. The current coordinates of the assembly / disassembly robot and the coordinates of the machine storage point are combined into a target coordinate information set. This information set guides the movement of the assembly / disassembly robot. Within the geographic space, the cloud server utilizes pathfinding algorithms (such as A* algorithm, Di...). The cloud server uses the JKStra algorithm (or a grid-based search algorithm) to find the optimal path from the assembly / disassembly robot's current location to its storage point. The algorithm considers various factors, such as path length, obstacles, and safety zones. After calculation, the cloud server generates the optimal path and translates it into commands or navigation points that the robot can understand. The cloud server then sends the optimal path to the robot, which, based on the received commands or navigation points, activates its mobility system (such as wheels or tracks) and moves along the optimal path to the corresponding storage point. During the movement, the cloud server can monitor the robot's position and status in real time and dynamically adjust the path or send new commands as needed. Finally, GIS technology, pathfinding algorithms, and robot control systems are integrated into the cloud server to form a complete equipment mobility management system.

[0073] The order delivery method includes: T1: The cloud server counts the current status of each AR device based on the AR device dataset, counts the number of currently executed repair orders based on the current status of each AR device, and counts the estimated completion time of each repair order based on the current number of repair orders, thereby obtaining the current AR device status set; T2: Based on the current AR device status set and repair orders, the distance between the repair site and each AR device is calculated and the arrival time is calculated. Then, the estimated completion time of all repair orders in each AR device is calculated and the arrival time is added. After sorting, the AR device with the time closest to the current time is selected as the target AR device for order delivery; T3: The cloud server sends the repair order to the target AR device through a private local area network.

[0074] It's important to note that based on the collected data, the cloud server statistically analyzes the current status of each AR device, including which devices are currently executing repair orders and which are idle. For devices executing repair orders, the cloud server counts the number of repair orders currently being executed for each device. Based on factors such as the type, difficulty, and historical completion time of each repair order, the cloud server calculates the estimated completion time for each order. This information—including the status of each AR device, the number of current repair orders, and the estimated completion time for each order—is integrated into a current AR device status set. For each repair order, the cloud server calculates the distance between the repair site and each AR device and calculates the arrival time based on the device's movement speed (which may be preset or acquired in real-time). For each AR device, the cloud server calculates the estimated completion time of all its repair orders and the time it takes to arrive at the repair site. The sum of these times represents the estimated completion time of the entire task chain if the order is assigned to this device. Among all AR devices, the device with the total time closest to the current time is selected as the target AR device for order delivery. This means that the device can respond to and complete the repair order as quickly as possible, while minimizing interference with its current task progress. The cloud server establishes a communication connection with the target AR device through a private LAN, encapsulates the relevant data of the repair order into a data packet of a specific format, and sends the encapsulated order data packet to the target AR device through the established communication connection. After receiving the order data packet, the target AR device sends a confirmation reply to the cloud server to ensure that the order has been successfully sent and received. Afterwards, AR device status monitoring, repair order management, path planning, communication protocols, etc. are integrated into the cloud server to form a complete order delivery system.

[0075] The method for creating the feature database is as follows: N1: Preprocess and integrate the drainage line information dataset and the fault dataset to obtain standard data. N2: Extract features from the standard data using image processing techniques, and classify and label the features to establish feature subsets. Features include the shape, color, and fault condition of the drainage line. N3: Build and define database tables based on the standard data and feature subsets. The database tables include a fault feature table, a fault type table, and a maintenance criterion table. N4: Update the standard data and feature subsets to the corresponding database tables in real time, thus obtaining the feature database.

[0076] It is important to note that, firstly, a dataset of drainage line information and a dataset of faults need to be collected. This data may come from different sensors, monitoring systems, or historical records. The collected data needs to be cleaned to remove duplicates, errors, or invalid data. This may include checking the integrity, consistency, and accuracy of the data. The cleaned drainage line information dataset and the fault dataset need to be integrated into a unified standard data format. This may involve data merging, transformation, and standardization operations to ensure that all data formats, units, and ranges are consistent for subsequent processing and analysis. Image processing techniques (such as edge detection, image segmentation, color analysis, etc.) are used to process the images or videos in the standard data to extract features such as the shape and color of the drainage lines. The extracted features need to be classified and labeled. For example, based on the shape of the drainage line, it can be classified as straight or curved; based on the color, it can be classified as red or green. At the same time, fault conditions also need to be labeled, such as whether there is breakage or corrosion. The classified and labeled features are then used to further analyze the data. The data is integrated into a feature subset for subsequent database table creation and data analysis. Based on the needs of the feature subset and standard data, the database structure is designed. This includes determining which database tables are needed, which fields each table contains, and the relationships between those fields. Necessary tables such as fault characteristic tables, fault type tables, and maintenance criterion tables are created in the database. These tables should be able to store relevant information from the feature subset and standard data. Field names, data types, lengths, constraints, and other attributes are defined for each table to ensure the table structure accurately reflects the data structure and relationships. Data import scripts or programs are written to import the standard data and feature subset into the corresponding database tables in real time. During the data import process, data validation is performed to ensure data accuracy and integrity. If errors or abnormal data are found, they should be processed and corrected promptly. The database is regularly updated and maintained, including adding new data, deleting outdated data, and optimizing query performance. Simultaneously, attention must be paid to database backup and recovery strategies to ensure data security.

[0077] like Figure 3As shown, the method for generating the maintenance report includes: Y1: Extracting key features based on survey information using image processing technology and integrating sensor data from the survey information set to obtain a survey information set; Y2: Matching key features with a feature database to obtain corresponding features, then obtaining the corresponding fault type based on the corresponding features and combining it with sensor data to obtain an evaluation report; Y3: Obtaining a maintenance report based on the evaluation report, maintenance criteria dataset, and survey information set.

[0078] It is important to note that for image or video data in the survey information, image processing techniques (such as edge detection, image segmentation, and feature extraction algorithms) are used to extract key features. These features may include the shape, color, texture, and abnormal areas of the equipment. Data from different sensors (such as temperature readings, pressure readings, and vibration frequencies) are integrated to form a unified survey information set. This information set contains multifaceted status information of the equipment. The extracted key features are matched with features in a feature database containing feature data of various normal and fault states of the equipment. By comparison, the features that best match the current survey information can be found. Based on the matched features, the corresponding fault type is obtained from the feature database. This usually involves finding fault descriptions and classifications associated with the features. Based on sensor data and fault type, an assessment report is generated. The assessment report should describe in detail the nature of the fault, possible causes, and impact on the equipment status. According to the fault type identified in the assessment report, the maintenance guidelines dataset is queried. The maintenance guidelines dataset contains detailed maintenance steps, required tools, materials, and safety precautions for different fault types. Based on the assessment report, maintenance guidelines dataset, and survey information set, a maintenance report is written. The maintenance report includes: fault description, maintenance steps, required materials and tools, safety precautions, maintenance personnel information, maintenance time, and location. After the maintenance report is written, it undergoes internal review to ensure its accuracy and completeness. After approval, the maintenance report is issued to relevant personnel (such as maintenance personnel and equipment administrators) to carry out maintenance work.

[0079] The AR device establishes a connection with the controller by transmitting information through a temporarily created private local area network (PLAN). The PLAN is created as follows: M1: The cloud server identifies the AR device ID and the assembly / disassembly robot ID based on the control request, and then automatically allocates a temporary communication channel to match the IP of the AR device with the corresponding IP of the assembly / disassembly robot. M2: The cloud server configures network services and security measures for the temporary communication channel. M3: After the AR device issues a termination command, the cloud server receives the command and automatically cancels the temporary communication channel and the corresponding logistics network services and security measures.

[0080] It is important to note that the server configures necessary network services for the temporary communication channel, such as DHCP (Dynamic Host Configuration Protocol) for IP address allocation, DNS (Domain Name System) for domain name resolution, and possibly other network protocols and services. To ensure the security of data transmission, the cloud server needs to configure security measures for the temporary communication channel. These measures may include encrypted communication protocols (such as TLS / SSL), firewall rule settings, and access control list (ACL) management. These measures can effectively prevent unauthorized access and data leakage. After configuration, the cloud server can perform some basic tests to verify the normal operation of network services and the effectiveness of security measures.

[0081] The survey equipment includes infrared thermal imagers, high-definition cameras, laser rangefinders, and electromagnetic field detectors.

[0082] A control system for a high-voltage substation busbar disconnection and reconnection robot was constructed using the above methods. This system collects basic datasets, AR device datasets, robot datasets, fault datasets, and maintenance criterion datasets from the high-voltage substation and stores and analyzes them on a cloud server. The cloud server receives real-time fault datasets, automatically creates and dispatches maintenance orders to the AR device, and the operator wears the AR device to control the disconnection and reconnection robot. The surveying equipment integrated into the disconnection and reconnection robot collects information on-site and uploads it to the cloud server. The cloud server generates a maintenance report based on this information, and the operator then controls the disconnection and reconnection robot to complete the maintenance according to the maintenance report.

[0083] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. A robot control method for dismantling and assembling busbars in high-voltage substations, characterized in that: The control method includes: Data collection: Acquire basic datasets for high-voltage substations, AR equipment datasets, robot datasets, fault datasets, and maintenance guideline datasets. The fault datasets include real-time fault datasets and historical fault datasets. The basic datasets for high-voltage substations include diversion line information datasets. Server setup: Set up a cloud server with a database to store basic datasets for high-voltage substations, AR equipment datasets, robot datasets, fault datasets, and maintenance guidelines datasets. The cloud server also contains the geospatial data of the high-voltage substations and establishes a feature database based on the fault datasets. Order dispatch: After obtaining the real-time fault dataset, the cloud server creates a repair order, which is then dispatched to the AR device according to the order dispatch method. On-site survey and analysis: The operator wears an AR device and controls the disassembly and assembly robot to conduct on-site surveys according to the equipment operation method. The disassembly and assembly robot is equipped with survey equipment to obtain survey information and upload it to the cloud server. The cloud server generates a maintenance report based on the survey information and sends it to the AR device. On-site repair: The operator uses AR equipment and, based on the repair report, operates the disassembly and assembly robot to perform repair work according to the equipment operation method; The equipment control method includes: S1: Establish connection. Each assembly / disassembly robot is equipped with an independent controller. AR devices can quickly connect to the corresponding controllers using a quick connection method. S2: Control commands. The operator uses the AR device to create a set of commands to control the designated assembly / disassembly robot to perform work in a fixed sequence, and the command set is stored on the AR device. S3: Release the device. The AR device sends a termination command to the controller on the designated assembly / disassembly robot based on the command set. After receiving the termination command, the designated assembly / disassembly robot moves to the designated position according to the device movement method.

2. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The fast connection method includes: A1: The cloud server obtains the current location and status information of the assembly / disassembly robot based on the robot dataset to get the device status set, and sends the device status set to the AR device; A2: Based on the maintenance order, the operator selects the disassembly / assembly robot that best matches the current location information and current status information from the equipment status set and sends a control request; A3: After the cloud service accepts the control request, it establishes a temporary control relationship between the designated assembly / disassembly robot and the AR device.

3. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The method for creating the command set includes: B1: The operator creates a command framework using the AR device based on the AR device dataset. The command framework is filled with basic operation methods and custom command methods. Both the basic operation methods and custom command methods are set in multiple ways and are matched one by one with different types of disassembly and assembly robots. B2: Operators can add their own required commands using the AR device's custom command method, thereby obtaining the executable command set for different assembly and disassembly robots; B3: Operators use AR devices to add command operation rules, allowing basic operation methods, custom command methods, and executable command sets to run within the rules.

4. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The device relocation method includes: C1: The cloud server uses GIS technology to establish the geospatial data of the high-voltage substation based on the basic dataset of the high-voltage substation. Multiple machine storage points are set up in the geospatial data, and each machine storage point is used to store a dedicated disassembly and assembly robot. C2: The cloud server obtains the current coordinate information of the released disassembly and assembly robot, and obtains the corresponding machine storage point coordinate information, thereby obtaining the target coordinate information set; C3: The cloud server uses a pathfinding algorithm based on geospatial information to find and generate the best movement path. The released disassembly and assembly robots then move to the corresponding machine storage point according to the best movement path.

5. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The order delivery method includes: T1: The cloud server uses the AR device dataset to count the current status of each AR device, counts the number of currently executed repair orders based on the current status of each AR device, and counts the estimated completion time of each repair order based on the current number of repair orders, thereby obtaining the current AR device status set; T2: Calculate the distance between the repair site and each AR device based on the current AR device status set and repair orders, and calculate the arrival time. Then, calculate the sum of the estimated completion times of all repair orders in each AR device and add the arrival time. After sorting, select the AR device with the time closest to the current time as the target AR device for order delivery. T3: The cloud server sends the repair order to the target AR device via a private local area network.

6. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The method for creating the feature database is as follows: N1: Standard data is obtained by preprocessing and integrating the drainage line information dataset and the fault dataset; N2: Based on standard data, features are extracted using image processing techniques, and the features are classified and labeled to establish a feature subset. The features include the shape, color, and fault condition of the drainage line. N3: Establish database tables based on standard data and feature subsets, and define the database tables, which include a fault feature table, a fault type table, and a maintenance criterion table; N4: Based on the database tables, standard data and feature subsets are updated to the corresponding database tables in real time, thereby obtaining the feature database.

7. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The method for generating the maintenance report includes: Y1: Based on the survey information, key features are extracted using image processing technology, and sensor data from the survey information set are integrated to obtain the survey information set; Y2: Based on key features and feature database, corresponding features are obtained by matching, and then corresponding fault types are obtained based on the corresponding features and combined with sensor data to obtain an evaluation report; Y3: The maintenance report is obtained based on the assessment report, maintenance criteria dataset, and survey information set.

8. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The AR device establishes a connection with the controller by transmitting information through a temporarily created private local area network (PLAN). The method for creating the PLAN includes: M1: The cloud server identifies the AR device ID and the assembly / disassembly robot ID based on the control request, and then automatically allocates a temporary communication channel to match the IP of the AR device with the corresponding IP of the assembly / disassembly robot; M2: Cloud servers configure network services and security measures for temporary communication channels; M3: After the AR device issues the end command, the cloud server receives the command and automatically cancels the temporary communication channel, as well as the corresponding logistics network services and security measures.

9. The robot control method for dismantling and assembling a high-voltage substation busbar as described in claim 1, characterized in that: The surveying equipment includes an infrared thermal imager, a high-definition camera, a laser rangefinder, and an electromagnetic field detector.

10. A robot control system for dismantling and assembling busbars in high-voltage substations, characterized in that: The method for controlling the dismantling and assembly robot of the high-voltage substation busbar lead-in line as described in any one of claims 1-9 is used. It collects basic datasets of the high-voltage substation, AR equipment datasets, robot datasets, fault datasets, and maintenance criterion datasets, and stores and analyzes them on a cloud server. The cloud server receives real-time fault datasets, automatically creates and dispatches maintenance orders to the AR equipment, and the operator wears the AR equipment to control the dismantling and assembly robot. The surveying equipment integrated into the dismantling and assembly robot collects information on-site and uploads it to the cloud server. The cloud server generates a maintenance report based on the report, and the operator then controls the dismantling and assembly robot to complete the maintenance according to the maintenance report.

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