Intelligent auxiliary system and method for secondary operation

Abstract

The invention relates to the field of power systems, in particular to an intelligent auxiliary system and method for secondary operation. The system comprises a server side and a man-machine interaction side connected with the server side. The server is configured with a YOLOv5 model and is used for performing target identification on the electronic drawing, identifying terminal strip and wiring information and obtaining position information of the terminal strip and the wiring information; the server is configured with an openCV machine vision technology and is used for receiving the obtained position information and carrying out image segmentation according to the position information to obtain segmented images; the server side is configured with an OCR technology and is used for carrying out character recognition, storage and verification on the segmented image; the server side is configured with a pressing plate state recognition algorithm for analyzing whether the pressing plate is correctly put and withdrawn; the server is configured with an intelligent substation configuration file visualization tool; and the infrared temperature measurement module is used for protecting temperature measurement of the device. According to the invention, the time cost, the labor cost and the economic cost are saved, and the system stability is improved.

Description

Technical Field

[0001] The present invention relates to the field of power systems, and particularly to an intelligent auxiliary system and method for secondary operations. Background Art

[0002] In the power system, secondary operations refer to operations such as configuration, commissioning, and maintenance of relay protection and control equipment in substations, which are crucial for ensuring the safe and stable operation of the power system. With the development of technology, especially the progress of AI and deep learning technologies, the traditional operation mode relying on manual verification urgently needs to be reformed to improve work efficiency and accuracy. In the prior art, secondary operations in substations face several challenges: First, due to the lack of automated tools, operators need to manually check the secondary circuits on site against the drawings, which is not only time-consuming but also error-prone. Second, the incompatibility problem of intelligent station SCD files makes file review difficult and affects the operation efficiency. In addition, it is difficult to detect potential hazards in long-term energized circuits, and manual inspections are difficult to cover all problems, such as wear of secondary wires and missing jumpers. The existence of these problems not only increases the workload of operators but also poses a threat to the safe and stable operation of the power system.

[0003] In response to the above problems, although some automated technologies have been proposed, such as an automatic inspection system and method for the wiring of secondary system equipment cabinets in substations (patent publication number CN108320287A), which realizes rapid elimination of wiring errors and improves inspection capabilities through the combination of cabinet wiring inspection and an electronic drawing server. However, these technologies are often limited to single functions, such as simple image recognition or single data processing, and lack an integrated solution to comprehensively improve the intelligence level of secondary operations.

[0004] In addition, another method, system, and device for positioning terminal block wiring labels (patent publication number CN117541653A) discloses a method for extracting wiring label features and determining updated wiring labels and their position information through image processing and a target recognition model. However, it still fails to provide a comprehensive intelligent auxiliary solution for secondary operations.

[0005] Therefore, it is necessary to develop an intelligent auxiliary system and method for secondary operations to solve the above problems. Summary of the Invention

[0006] The purpose of the present invention is to provide an intelligent auxiliary system and method for secondary operations to solve the problems of large manual verification workload, low efficiency, and easy errors in traditional power system secondary operations.

[0007] To achieve the above purpose, the following technical solutions are adopted.

[0008] An intelligent auxiliary system for secondary operations includes

[0009] A server and a human-computer interaction terminal connected to the server;

[0010] The server is configured with a YOLOv5 model for target recognition of electronic drawings, identifying terminal blocks and wiring information, and obtaining the position information of the terminal blocks and wiring information;

[0011] The server is configured with openCV machine vision technology for receiving the obtained position information and performing image segmentation according to the position information to obtain the segmented image;

[0013] The server is configured with OCR technology for text recognition, storage, and verification of the segmented image;

[0014] The server is configured with a busbar protection state recognition algorithm for analyzing whether the busbar protection is correctly put into or withdrawn;

[0015] The server is configured with a visualization tool for intelligent substation configuration files to improve the compatibility and working efficiency of SCD configuration files from different manufacturers;

[0016] The server is configured with a visualization tool for intelligent substation configuration files to improve the compatibility and working efficiency of SCD configuration files from different manufacturers;

[0017] It further includes an infrared temperature measurement module for temperature measurement of protection devices.

[0018] Optionally, implementing the openCV machine vision technology further includes,

[0019] An image preprocessing module for preliminarily processing the image of the electronic drawing received by the server, including grayscale conversion and contrast enhancement, to improve the accuracy of subsequent image segmentation;

[0020] A position information parsing module: for parsing the position information of the terminal blocks and wiring information provided by the YOLOv5 model and converting it into image coordinates;

[0021] An image segmentation module: segmenting the image according to the coordinates provided by the position information parsing module to extract the images of the terminal blocks and wiring information;

[0022] A result storage module: for storing the results of image segmentation, including the segmented image data and feature data, for subsequent text recognition and verification;

[0023] Optionally, it further includes a secondary segmentation module for secondarily segmenting the image segmented by the image segmentation module based on each terminal name to obtain the segmented image.

[0024] Optionally, it further includes a dictionary storage module for storing the recognition data obtained by text recognition of the segmented image in the format of a dictionary.

[0025] Optionally, it further includes a verification module, which is used to identify the physical terminal name and the name of the opposite end of the physical connection based on the terminal number, and perform corresponding verification with the drawing terminal name and the name of the opposite end of the drawing connection of the corresponding terminal number in the electronic drawing.

[0026] Optionally, the infrared temperature measurement module is numbered with a temperature measurement range of -15° to +80°.

[0027] Optionally, it further includes a handheld terminal, which includes the following modules:

[0028] Image acquisition module: used to take pictures on-site to acquire images of the terminal block and wiring information;

[0029] Data transmission module: used to wirelessly transmit the acquired image data to the server.

[0030] Optionally, the human-computer interaction terminal and the infrared temperature measurement module are set on the handheld terminal. The human-computer interaction terminal is used to display the processing results returned by the server, including the text recognition result, the platen status recognition result, and the visualization information of the intelligent substation configuration file. It is also used to receive the instructions and feedback information input by the user, as well as send requests and interaction data to the server.

[0031] A secondary operation intelligent assistance method includes the following steps

[0032] Use the YOLOv5 model configured by the server to perform target recognition on the electronic drawing, identify the terminal block and wiring information, and obtain the position information of the terminal block and wiring information;

[0033] Utilize the openCV machine vision technology of the server to perform image segmentation on the electronic drawing image according to the obtained position information to obtain the segmented image;

[0034] Through the OCR technology of the server, perform text recognition on the segmented image, and store the recognition result in the dictionary storage module in dictionary format;

[0035] Use the verification module to retrieve the recognition result stored in the dictionary storage module based on the terminal number of the physical object. The recognition result includes the drawing terminal name and the name of the opposite end of the drawing connection of the corresponding terminal number in the electronic drawing; then perform corresponding verification on the recognized physical terminal name and the name of the opposite end of the physical connection with the drawing terminal name and the name of the opposite end of the drawing connection of the corresponding terminal number;

[0036] Use the platen status recognition algorithm configured by the server to analyze whether the platen is correctly inserted and withdrawn;

[0037] Set up the intelligent substation configuration file visualization tool of the server to adapt to the SCD configuration file of the current manufacturer;

[0038] The infrared temperature measurement module integrated through the human-machine interaction terminal measures the temperature of the protection device, and the temperature measurement range is between -15°C and +80°C.

[0039] Optionally, the platen status recognition algorithm specifically includes the following steps.

[0040] Preset the operating status information of the platen, that is, determine the standard position or status that the platen should be in during normal operation.

[0041] Real-time monitor and record the current actual position or status of the platen through image recognition technology.

[0042] Compare the obtained actual platen status information with the preset platen operating status information to determine the difference between the actual status and the preset standard status.

[0043] Based on the comparison result, analyze whether the platen is correctly inserted and withdrawn. Specifically:

[0044] If the actual status of the platen is consistent with the preset operating status, it is determined that the platen is in the correct insertion and withdrawal state.

[0045] If the actual status of the platen is inconsistent with the preset operating status, it is determined that the platen is in the incorrect insertion and withdrawal state, and an alarm signal or prompt message is generated.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The secondary operation intelligent auxiliary system of this application integrates the YOLOv5 model, openCV machine vision technology, and OCR technology, realizing automatic target recognition and image segmentation of electronic drawings, as well as automatic text recognition and verification of the segmented images. The application of these technologies greatly reduces the workload of manual line checking and proofreading, improving the efficiency and accuracy of the operation. Compared with traditional manual verification, this system can complete complex image recognition and data processing tasks in a short time, reducing the possibility of human errors, thereby improving the accuracy of the operation.

[0048] This system improves the compatibility and working efficiency of SCD configuration files from different manufacturers by configuring an intelligent substation configuration file visualization tool. The use of this tool enables on-site personnel to view and process the configuration files of each manufacturer without having to be familiar with various tools from different manufacturers. It greatly simplifies the operation process and improves the working efficiency.

[0049] Through the application of automation technology, this system reduces the dependence on professional personnel and saves a large amount of labor costs. At the same time, due to the reduction of on-site operation time and personnel configuration, it also reduces the power grid operation risks caused by operations, thereby saving economic costs.

[0050] This system effectively reduces the power grid risk and improves the system stability by shortening the large-scale on-site working time, which is of great significance for ensuring the continuous and stable power supply of the power system. The verification module greatly improves the verification efficiency and reduces the errors and time consumption of manual verification by automatically comparing the physical terminals with the drawing information. The temperature measurement range of the infrared temperature measurement module covers -15°C to +80°C, meeting the temperature monitoring requirements of substation equipment under extreme temperatures and enhancing the system security. The handheld terminal integrates image acquisition and data transmission functions, enabling on-site operators to quickly collect images and transmit them to the server for processing, improving the flexibility and efficiency of on-site operations. The human-machine interaction terminal is integrated into the handheld terminal, allowing on-site personnel to directly receive the processing results and send interactive data on the handheld terminal, optimizing the human-machine interaction experience and enhancing the operation convenience. Through automated method steps, the whole process automation from drawing recognition to temperature monitoring is achieved, greatly improving the overall efficiency and accuracy of secondary operations. Through the application of OCR technology and the verification module, the accuracy of the recognized data is ensured and the operation quality is improved. The platen status recognition algorithm can monitor and judge the platen status in real time, generating alarm signals or prompt messages in a timely manner, improving the system response speed and security.

[0051] Save time cost

[0052] 1) Currently, the average wire checking time for a single panel is 1 hour; after applying this system, it only takes 5 minutes to complete wire checking, saving 91.67% of the time cost.

[0053] 2) Currently, it takes about 20 minutes for secondary equipment professional inspection, infrared temperature measurement, and platen check for a single panel; after applying this system, it is expected to be reduced to 5 minutes, saving 75% of the time cost.

[0054] 3) Currently, there are as many as 7 types of significant differences among the intelligent station configuration file tool software of different manufacturers, which is difficult for secondary professionals to be familiar with and apply all; after applying this system, they can only learn the software of this system to view the configuration files of each manufacturer, saving 85.71% of the learning time cost.

[0055] Save labor cost

[0056] After applying this system, the work efficiency of secondary personnel can be greatly improved in the secondary professional overhaul and technical transformation work, reducing the single staff configuration. With the implementation of operation and maintenance integration, operation and maintenance personnel can also complete the correctness verification of secondary circuit wiring and the access of intelligent station configuration files, and it is expected to save more than 50% of the labor cost.

[0057] Save economic cost

[0058] After applying this system, the time and personnel input at various operation sites can be significantly reduced, the power outage time of equipment can be decreased, and the power grid operation risk caused by failures can be lowered. Calculated based on a municipal power company, the comprehensive cost can be saved by 2 million yuan annually. If it is promoted for application nationwide, it is estimated that the comprehensive cost can be saved by 200 million yuan annually.

[0059] Improve system stability

[0060] The shortening of large-scale on-site working time can also effectively reduce the power grid risk and improve system stability. Description of the drawings

[0061] Figure 1 It is a schematic diagram of modules according to an embodiment of an intelligent auxiliary system for secondary operations of the present invention.

[0062] Figure 2 It is a schematic diagram of the step flow according to an embodiment of an intelligent auxiliary method for secondary operations of the present invention. Detailed implementation manners

[0063] The present invention will be described in detail below with reference to the drawings and in conjunction with embodiments. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0064] The following detailed descriptions are all exemplary descriptions, aiming to provide further detailed descriptions of the present invention. Unless otherwise specified, all technical terms adopted by the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which the present application belongs. The terms used in the present invention are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention.

[0065] Embodiment 1

[0066] As Figure 1 shown, an intelligent auxiliary system for secondary operations is as follows:

[0067] This system mainly includes a server and a human-computer interaction terminal connected to the server. The server, as the core processing unit of the system, undertakes the functions of data processing, analysis, and storage, while the human-computer interaction terminal provides a user interface, enabling operators to interact with the system.

[0068] The server is configured with a YOLOv5 model, which is an advanced object detection algorithm used for target recognition of electronic drawings. Specifically, the YOLOv5 model can identify the terminal blocks and wiring information in the drawings and accurately obtain the position information of these components. This position information is crucial for subsequent image processing steps.

[0069] Furthermore, the server is also configured with openCV machine vision technology, which receives the position information provided by the YOLOv5 model and performs precise image segmentation on the drawing images based on this information. The segmented images will only contain the terminal block and wiring information, providing clear image input for the subsequent text recognition step.

[0070] The server is also configured with OCR technology, which is responsible for recognizing, storing, and verifying the text in the segmented images. Through OCR technology, the system can convert the text information in the images into editable and storable text data, facilitating subsequent data processing and analysis.

[0071] In addition, the server is also configured with a busbar protection status recognition algorithm, which judges whether the busbar protection is correctly switched in or out by analyzing the difference between the actual status of the busbar protection and the preset standard status. This function is crucial for ensuring the safe operation of the power system.

[0074] The server is also configured with a visualization tool for intelligent substation configuration files, which can improve the compatibility and working efficiency of SCD configuration files from different manufacturers. Through this tool, operators can easily manage and view SCD configuration files from different manufacturers without worrying about file formats and compatibility issues.

[0075] Finally, the system also includes an infrared temperature measurement module, which is used to measure the temperature of the protection device, and the temperature measurement range is between -15°C and +80°C. This module can monitor the temperature status of the protection device in real time, providing additional guarantee for the safe operation of the system.

[0076] In summary, through the integration of a variety of advanced technologies, this intelligent auxiliary system for secondary operations realizes the full-process automation from drawing recognition, image segmentation, text recognition, busbar protection status monitoring to temperature measurement, greatly improving the efficiency and accuracy of secondary operations in the power system. Through specific technical implementation methods, the system can clearly and completely execute its functions and reach the level of practical implementation.

[0077] As a specific example, the openCV machine vision technology includes the following key modules:

[0078] Image preprocessing module: This module is responsible for the preliminary processing of the electronic drawing images received by the server. The specific operations include converting the images into grayscale images to reduce the data volume for subsequent processing and improve the processing speed. At the same time, through contrast enhancement technology, the visibility of the terminal block and wiring information in the images is enhanced, enabling the subsequent image segmentation steps to more accurately identify and locate the target objects.

[0079] Position Information Parsing Module: The function of this module is to parse the position information of the terminal block and wiring information provided by the YOLOv5 model. The positioning information output by the YOLOv5 model usually includes bounding box coordinates, and the Position Information Parsing Module converts these coordinates into precise positions in the image coordinate system, providing an accurate positioning basis for image segmentation.

[0080] Image Segmentation Module: According to the coordinates provided by the Position Information Parsing Module, the Image Segmentation Module performs image segmentation operations. This module uses image segmentation algorithms in the openCV library, such as threshold-based segmentation, region growing algorithms, or edge detection algorithms, to precisely segment the images of the terminal block and wiring information from the preprocessed images. The segmented images will only contain the required terminal block and wiring information, providing a clear input for the subsequent text recognition step.

[0081] Result Storage Module: This module is responsible for storing the results of image segmentation, including the segmented image data and feature data. The stored data will be used for subsequent text recognition and verification steps to ensure data integrity and traceability in the system. The Result Storage Module may use methods such as databases or file systems for data storage to facilitate data management and access.

[0082] As a preferred example of the above example, it further includes a secondary segmentation module, which is part of the openCV machine vision technology and is used to perform further refined segmentation on the preliminary segmented images processed by the Image Segmentation Module.

[0083] After the Image Segmentation Module successfully segments the electronic drawing image into preliminary segmented images containing the terminal block and wiring information, the secondary segmentation module is activated for more detailed processing.

[0084] The secondary segmentation module first uses OCR technology to identify the terminal names in the preliminary segmented images. This process involves

[0086] detecting and recognizing the text in the image and converting the image into text information.

[0087] To more precisely locate the terminal names and the corresponding wiring information, the secondary segmentation module performs binarization processing on the preliminary segmented images. This step converts the image into an image containing only black and white pixels by setting a threshold, where black represents the terminal names and wiring information, and white represents the background.

[0088] Based on the binarization, the secondary segmentation module determines the exact positions of each terminal name in the image through image processing techniques such as edge detection or region growing algorithms.

[0089] Based on the position information of the terminal names, the secondary segmentation module performs secondary segmentation on the preliminarily segmented image. This process involves drawing cutting lines in the image to separate each terminal name and its corresponding wiring information into independent image segments.

[0090] After secondary segmentation, the module may perform edge smoothing or other optimization operations on the obtained image segments to improve the accuracy of subsequent text recognition.

[0091] To ensure the accuracy of segmentation, the secondary segmentation module will verify the obtained image segments. This may include checking whether the image segments contain complete terminal names and wiring information, and whether there is unnecessary background interference.

[0092] After verification, the secondary segmentation module stores the segmented image for subsequent text recognition and verification. The storage format may be a database, a file system, or other formats suitable for storing image and text data.

[0093] Through the above steps, the secondary segmentation module can accurately segment the image of the terminal block and wiring information into independent segments based on each terminal name, providing a higher level of image processing capabilities for the intelligent auxiliary system for secondary operations, thereby improving the performance and reliability of the entire system.

[0094] As a preferred example, after the OCR technology performs text recognition on the segmented image, the obtained recognition data includes the text content and its position information in the original image. These data are the basis for subsequent step processing.

[0095] The dictionary storage module formats the recognized text data into key-value pairs. The key can be the terminal block number or terminal name, and the value is the corresponding text content, such as wiring information or other relevant marks. Create a dictionary structure in the database or memory to store and manage the key-value pairs. This dictionary structure can be implemented based on a hash table to ensure the efficiency of data retrieval. Store the formatted key-value pairs into the dictionary structure. For each terminal block or wiring information, there is a corresponding entry that contains all relevant recognized data. Before storing the data, the dictionary storage module validates the recognized data to ensure its integrity and accuracy. This may include verifying the recognition results, such as by comparing the recognized text with known reference data. If an entry with the same key already exists, the dictionary storage module updates the data of the existing entry to ensure the latest status of the information. This is particularly important in a dynamic environment to ensure the timeliness of the data. Provide a retrieval function that allows other modules of the system to quickly retrieve the corresponding text data based on the terminal block number or name. The retrieval results can be used for subsequent verification and analysis. The dictionary storage module can be synchronized with an external database to ensure the sharing of the latest recognized data among multiple systems or modules. To prevent data loss, the dictionary storage module implements regular backups and provides a data recovery mechanism to protect critical data from accidental loss. Provide a user interface that allows operators to view, edit, and verify the recognized data stored in the dictionary, enhancing the interactivity and flexibility of the system.

[0096] Through the above steps, the dictionary storage module can store and manage a large amount of recognized data in a structured and orderly manner, providing a reliable and efficient data management solution for the intelligent auxiliary system for secondary operations.

[0097] As a specific example, the verification module is used to verify the physical terminal name and its connected opposite-end name against the corresponding information on the electronic drawing to ensure the consistency between the on-site physical object and the design drawing.

[0098] The verification module first retrieves the stored recognized data from the dictionary storage module, which includes the numbers, names of physical terminals, and the names of the connected opposite ends. At the same time, this module also obtains the corresponding terminal information on the electronic drawing from the visualization tool for intelligent substation configuration files. The verification module matches the numbers of physical terminals with the numbers of drawing terminals to ensure that each physical terminal can find a corresponding number on the drawing.

[0099] For each matched terminal, the verification module checks whether the physical terminal name is consistent with the drawing terminal name, and whether the physical connected opposite-end name is consistent with the drawing connected opposite-end name.

[0100] During the verification process, if any inconsistencies are found, the verification module will mark them as anomalies and record the specific information of the inconsistencies, such as terminal numbers, terminal names, names of the connected counterparts, etc.

[0101] The verification module records the verification results in the system, including information on successful matches and anomaly information. These records can be used for subsequent analysis and reporting.

[0102] Based on the verification results, the verification module generates a verification report that details the status of all verification items, including successfully matched items and anomaly items.

[0103] The verification module provides a real-time feedback mechanism that can immediately notify the operator when an anomaly is detected, so that measures can be taken promptly on-site.

[0104] During the verification process, if it is necessary to update the drawing information or physical information, the verification module will trigger a data update process to ensure that all data remains up-to-date.

[0105] The verification module allows the verification logic to be adjusted according to actual needs, such as adding new verification rules or modifying existing verification rules.

[0106] The verification module provides a user interface that enables the operator to manually input information, view verification results, handle anomaly items, and confirm verification results.

[0107] The verification module can ensure the consistency between physical terminals and drawing terminals in secondary operations, improving the accuracy and reliability of operations.

[0108] As a specific example, an infrared temperature measurement module is used for temperature measurement of protection devices, and its temperature measurement range is from -15°C to +80°C.

[0109] The infrared temperature measurement module is integrated into the handheld terminal of the intelligent auxiliary system for secondary operations and has a non-contact temperature measurement function. It can accurately detect hot spots of power equipment within the range of -15°C to +80°C. The temperature measurement range of the infrared temperature measurement module is set from -15°C to +80°C, which covers the temperature changes that may occur in power equipment during normal operation and abnormal conditions, ensuring comprehensive monitoring of the equipment status.

[0110] The infrared temperature measurement module has high measurement accuracy and can provide a temperature measurement accuracy of ±1°C or better to ensure the reliability of temperature readings. The infrared temperature measurement module can monitor the temperature changes of power equipment in real time and transmit the data to the server in real time for further analysis. The infrared temperature measurement module automatically collects temperature data according to the preset data collection frequency, which can be adjusted according to actual monitoring needs to adapt to different monitoring scenarios. When the temperature detected by the infrared temperature measurement module exceeds the normal range, the system will automatically trigger an alarm mechanism to remind the operator of possible equipment failures or abnormalities. All collected temperature data is stored in the database on the server for historical data query, trend analysis, and maintenance records. The infrared temperature measurement module has an environmental factor correction function and can automatically correct the measurement results according to environmental conditions such as temperature and humidity to improve the measurement accuracy. The infrared temperature measurement module interacts with the operator through the user interface on the handheld device, providing real-time temperature display, historical data query, and alarm information prompts.

[0111] Module integration and compatibility: The design of the infrared temperature measurement module takes into account compatibility with other system modules and can be seamlessly integrated into the intelligent auxiliary system for secondary operations and can communicate effectively with the server software.

[0112] Through the above steps, the infrared temperature measurement module can provide accurate temperature monitoring functions for the intelligent auxiliary system for secondary operations, enhance the monitoring ability of the status of power equipment, and improve the safety and reliability of the power system.

[0113] As a preferred example, the handheld device includes an image acquisition module and a data transmission module for taking images of the terminal block and wiring information on site and wirelessly transmitting them to the server. The handheld device is configured with a high-resolution image acquisition module, which includes one or more cameras and can clearly capture images of the terminal block and wiring information. The camera has autofocus and optical zoom functions to meet the shooting requirements at different distances and angles.

[0114] The operator uses the image acquisition module of the handheld device at the substation site to take pictures of the terminal block and wiring information according to the system prompts or manual operations. The image acquisition module can capture high-definition images and provide on-site previews.

[0115] The image acquisition module is built-in with an image quality control algorithm to ensure that the captured images meet the system's requirements for resolution and clarity. If the image does not meet the preset standards, the system will prompt to retake the picture.

[0116] The data transmission module of the handheld device is responsible for transmitting the collected image data to the server through the wireless network. This module supports multiple wireless communication protocols such as Wi-Fi, 4G / 5G, etc. to ensure the stability and security of data transmission.

[0117] Through the above steps, the handheld device can provide efficient and reliable on-site image acquisition and data transmission functions for the secondary operation intelligent assistance system, greatly improving the efficiency and accuracy of on-site operations.

[0118] As a preferred example of the above example, the human-machine interaction terminal is integrated into the handheld device and works in cooperation with the infrared temperature measurement module. It is used to display the processing results returned by the server, receive instructions and feedback information input by the user, and send requests and interaction data to the server. The human-machine interaction terminal is equipped with a high-resolution touch display screen for displaying the processing results returned by the server, including text recognition results, platen status recognition results, and visualization information of the intelligent substation configuration file. The user interface is designed to be intuitive and easy to operate to ensure that operators can quickly understand and use it.

[0119] After the server finishes processing, it wirelessly transmits the result data to the human-machine interaction terminal of the handheld device. The human-machine interaction terminal displays these results through a graphical interface, including text information, status indicators, and graphical displays of configuration files. The human-machine interaction terminal provides a virtual keyboard or touch screen handwriting input function for receiving instructions and feedback information input by the user. These inputs can be confirmation operations, modification instructions, or annotations on the results. The human-machine interaction terminal sends the user's inputs and requests to the server through a wireless communication module. This includes confirmation of the server's processing results, reporting of abnormal situations, and requests for further analysis.

[0120] The human-machine interaction terminal implements a real-time feedback mechanism. When the user performs an operation or submits information, the system will immediately give visual or auditory feedback, such as displaying a confirmation message or emitting a prompt tone.

[0121] The human-machine interaction terminal and the infrared temperature measurement module are integrated in the same handheld device, allowing operators to directly control the infrared temperature measurement module through the human-machine interaction terminal on-site for temperature measurement and view the measurement results in real time.

[0122] The human-machine interaction terminal can synchronize data with the server to ensure that the displayed information is up-to-date. After the server updates the processing results, the human-machine interaction terminal can automatically or manually request an update of the data.

[0123] The human-machine interaction terminal has error handling capabilities. When a communication error or data transmission problem occurs, the system will prompt the operator through the interface and provide suggestions or operations for error resolution.

[0124] Through the above steps, the human-machine interaction terminal can provide an intuitive and efficient user interaction interface for the secondary operation intelligent assistance system, enabling operators to conveniently receive processing results, input instructions, and feedback information on-site.

[0125] Embodiment 2

[0126] As Figure 2 shown, the specific implementation of an intelligent auxiliary method for secondary operation is as follows:

[0127] Start the YOLOv5 model configured on the server to perform object recognition on the uploaded electronic drawing.

[0128] The YOLOv5 model automatically recognizes the terminal blocks and wiring information in the drawing and accurately obtains the position information of these components.

[0129] The position information includes the coordinates of the terminal blocks and wiring, providing an accurate reference for the next image segmentation.

[0130] Using the openCV machine vision technology on the server, perform accurate image segmentation on the drawing image according to the position information provided by the YOLOv5 model.

[0131] The result of image segmentation is an image containing individual terminal blocks and wiring information, providing clear image input for the subsequent text recognition step.

[0132] Through the OCR technology on the server, recognize the text in the segmented image.

[0133] Store the text results recognized by the OCR technology in the dictionary storage module in dictionary format, where the key is the terminal number and the value is the corresponding terminal name and wiring information.

[0134] Use the verification module to retrieve the corresponding recognition results in the dictionary storage module according to the terminal numbers of the on-site physical objects.

[0135] The verification module compares the physical terminal names and the names of the physical connection counterparts with the corresponding information in the electronic drawing to verify consistency. Any inconsistencies will be marked and recorded for subsequent analysis and correction.

[0136] Use the busbar protection state recognition algorithm configured on the server to analyze the difference between the actual state of the busbar protection and the preset standard state. The algorithm determines whether the busbar protection is correctly put into or withdrawn, and generates an alarm signal or prompt message when an abnormality is found.

[0137] Set up the visualization tool for the intelligent substation configuration file on the server to adapt to and display the SCD configuration file of the current manufacturer. The tool improves the compatibility and working efficiency of the SCD configuration files of different manufacturers, enabling operators to easily manage and view the configuration files.

[0138] The infrared temperature measurement module integrated through the human-machine interaction terminal measures the temperature of the protection device. The temperature measurement range of the temperature measurement module is between -15°C and +80°C, ensuring that it can cover the possible temperature changes of the protection device. The temperature measurement results are displayed in real time on the human-machine interaction terminal and can be wirelessly transmitted to the server for further analysis.

[0139] Through the above steps, the intelligent auxiliary method for secondary operation realizes the full-process automation from drawing recognition, image segmentation, character recognition, data verification, platen status monitoring to temperature measurement, greatly improving the efficiency and accuracy of secondary operation in the power system. The implementation method of this method is clear and complete, reaching the degree of actual implementability, providing a strong guarantee for the safe and stable operation of the power system.

[0140] As a preferred example, the specific implementation method of the platen status recognition algorithm, which is used to analyze whether the platen is in the correct on / off state.

[0141] The platen status recognition algorithm first needs to obtain the standard position or status information that the platen should be in during normal operation. This information may include the standard position of the platen, the expected status (such as on or off), and other relevant parameters.

[0142] These preset information are stored in the system database or configuration file for the algorithm to use in subsequent steps.

[0143] Using image recognition technology, such as the YOLOv5 model configured on the server, the actual position or status of the platen is monitored in real time.

[0144] The system captures the real-time image of the platen through the camera or other image acquisition devices integrated on the human-machine interaction terminal and transmits it to the server for processing.

[0145] The algorithm extracts the actual position or status information of the platen from the real-time image and records it.

[0146] The extracted information may include the current position of the platen, status markers, or other features that help determine the platen status.

[0147] The algorithm compares the extracted actual platen status information with the preset platen operation status information.

[0148] The comparison process involves checking whether the actual status is consistent with the preset status, including position matching, status consistency check, etc.

[0149] Based on the comparison result, the algorithm analyzes whether the platen is correctly on / off.

[0150] If the actual status of the platen is consistent with the preset operation status, the algorithm determines that the platen is in the correct on / off state and continues to monitor.

[0151] If the actual state of the pressure plate is inconsistent with the preset operating state, the algorithm determines that the pressure plate is in an incorrect switching state.

[0152] When the pressure plate is determined to be in an incorrect switching state, the algorithm generates an alarm signal or a prompt message.

[0153] The alarm signal or prompt message is displayed to the operator through the human-machine interface or sent to the relevant personnel through the system notification.

[0154] These messages include the state differences of the pressure plate, the possible impacts, and the recommended corrective measures.

[0155] The comparison results of all pressure plate states and the alarm information are recorded in the system log file for subsequent review and analysis.

[0156] The system can also generate a regular pressure plate state report for the management to review and take necessary maintenance measures.

[0157] Through the above steps, the pressure plate state recognition algorithm can accurately monitor and analyze the state of the pressure plate to ensure the safe and stable operation of the power system.

[0158] As is known by technical common sense, the present invention can be implemented by other embodiments that do not depart from its spirit or essential features. Therefore, the above-disclosed embodiments are illustrative in all aspects and not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are encompassed by the present invention.

Claims

1. A secondary operation intelligent auxiliary system, characterized in that: include, A server and a human-computer interaction terminal connected to the server; The server is configured with a YOLOv5 model to perform target recognition on the electronic version drawings, identify the terminal blocks and wiring information, and obtain the location information of the terminal blocks and wiring information; The server is equipped with openCV machine vision technology to receive the obtained position information, perform image segmentation according to the position information, and obtain the segmented image; The server is equipped with OCR technology to perform text recognition, storage and verification on the segmented images; The server is configured with a pressure plate status recognition algorithm to analyze whether the pressure plate is correctly inserted or retracted; The server is equipped with a smart substation configuration file visualization tool to improve the compatibility and work efficiency of SCD configuration files from different manufacturers; It also includes an infrared temperature measurement module for measuring the temperature of the protection device.

2. The secondary operation intelligent assistance system according to claim 1, characterized in that: Implementing openCV machine vision technology also includes, The image preprocessing module is used to perform preliminary processing on the image of the electronic version of the drawing received by the server, including grayscale conversion and contrast enhancement, so as to improve the accuracy of subsequent image segmentation; Position information parsing module: used to parse the position information of the terminal block and wiring information provided by the YOLOv5 model and convert it into image coordinates; Image segmentation module: segment the image according to the coordinates provided by the position information analysis module, and extract the image of the terminal block and wiring information; Result storage module: used to store the results of image segmentation, including segmented image data and feature data, for subsequent text recognition and verification.

3. The secondary operation intelligent assistance system according to claim 2, characterized in that: It also includes a secondary segmentation module for performing secondary segmentation on the initial segmented image segmented by the image segmentation module based on the name of each terminal segment to obtain a segmented image.

4. The secondary operation intelligent assistance system according to claim 1, characterized in that: It also includes a dictionary storage module, which is used to store the recognition data obtained by performing text recognition on the segmented image in a dictionary format.

5. The secondary operation intelligent assistance system according to claim 1, characterized in that: It also includes a verification module for identifying the physical terminal name and the physical connection counterpart name based on the terminal number, and verifying the correspondence between the drawing terminal name and the drawing connection counterpart name of the corresponding terminal number in the electronic drawing.

6. The secondary operation intelligent assistance system according to claim 1, characterized in that: The infrared temperature measurement module has a temperature measurement range of -15° to +80°.

7. The secondary operation intelligent assistance system according to claim 1, characterized in that: Also included is a handheld terminal, which includes the following modules: Image acquisition module: used to capture images of terminal blocks and wiring information on site; Data transmission module: used to wirelessly transmit the collected image data to the server.

8. The secondary operation intelligent assistance system according to claim 7, characterized in that: The human-computer interaction terminal and the infrared temperature measurement module are arranged on the handheld terminal. The human-computer interaction terminal is used to display the processing results returned by the server, including text recognition results, pressure plate status recognition results and visualization information of the smart substation configuration file, and is also used to receive instructions and feedback information input by the user, and send requests and interaction data to the server.

9. A secondary operation intelligent assistance method, based on a secondary operation intelligent assistance system according to any one of claims 1 to 8, characterized in that: The following steps are included: Use the YOLOv5 model configured on the server to identify the electronic version of the drawing, identify the terminal block and wiring information, and obtain the location information of the terminal block and wiring information; Using the openCV machine vision technology on the server side, the electronic version drawing image is segmented according to the acquired position information to obtain the segmented image; Through the OCR technology on the server side, the segmented image is recognized for text, and the recognition results are stored in the dictionary storage module in a dictionary format; Using the verification module, based on the terminal number of the physical object, the recognition result stored in the dictionary storage module is retrieved, wherein the recognition result includes the drawing terminal name of the corresponding terminal number of the electronic drawing and the drawing connection opposite terminal name; Then check the recognized physical terminal name and physical connection opposite terminal name against the drawing terminal name and drawing connection opposite terminal name of the corresponding terminal number; Use the pressure plate status recognition algorithm configured on the server to analyze whether the pressure plate is correctly inserted or retracted; Set up the server-side smart substation configuration file visualization tool to adapt to the current manufacturer's SCD configuration file; The temperature of the protection device is measured by the infrared temperature measurement module integrated in the human-computer interaction terminal, and the temperature measurement range is between -15° and +80°.

10. A secondary operation intelligent assistance method according to claim 9, characterized in that: The platen state recognition algorithm specifically includes the following steps: Preset the operating status information of the pressing plate, that is, determine the standard position or state that the pressing plate should be in during normal operation; Monitor and record the actual position or status of the pressing plate in real time through image recognition technology; Compare the acquired actual state information of the press plate with the preset operation state information of the press plate to determine the difference between the actual state and the preset standard state; Based on the comparison results, analyze whether the pressure plate is correctly inserted and retracted, specifically: If the actual state of the pressing plate is consistent with the preset running state, it is judged that the pressing plate is in the correct throwing and retracting state; If the actual state of the pressing plate is inconsistent with the preset operating state, the pressing plate is judged to be in an incorrect insertion or retraction state, and an alarm signal or prompt message is generated.

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