Real-time monitoring and diagnosing method and system for substation equipment

Abstract

The invention provides a transformer substation equipment real-time monitoring and diagnosing method and system, and the method comprises the steps: collecting a plurality of pieces of monitoring video data in a transformer substation in real time, and obtaining a panoramic view of the transformer substation; the method comprises the following steps: acquiring field sensor data of a transformer substation in real time, generating real-time equipment simulation data by using an improved digital twin model corresponding to the transformer substation, performing potential fault diagnosis on the transformer substation, and extracting real-time equipment image features of the transformer substation; based on the real-time equipment image features and the real-time equipment simulation data, the operation condition of the substation equipment is monitored in real time; and carrying out visual presentation. According to the method, the real-time equipment image features of the transformer substation can be extracted from the panoramic view, the improved digital twinborn model not only can synchronize the simulation data of the transformer substation equipment, but also can perform potential fault diagnosis, and meanwhile, the real-time equipment image features are compared with the synchronous real-time equipment simulation data, so that the fault diagnosis accuracy is improved. And a comprehensive and accurate real-time monitoring result can be obtained.

Description

Technical Field

[0001] The present invention relates to the field of power system technology, and specifically to a real-time monitoring and diagnosis method and system for substation equipment. Background Art

[0002] With the development of intelligent power system, higher requirements are put forward for real-time monitoring and diagnosis of substation equipment. Traditional monitoring methods usually rely on a single video source or sensor data, which has problems such as limited monitoring range and incomplete information, and it is difficult to meet the needs of comprehensive understanding and accurate diagnosis of substation equipment status.

[0003] Most of the existing real-time monitoring and diagnosis methods for substation equipment adopt the following means: (1) The single sensor data monitoring system monitors the status of substation equipment in real time by installing single-type sensors such as temperature sensors and humidity sensors at key parts of the equipment, and obtains information from a single data source such as temperature and humidity. The disadvantages of the single sensor data monitoring system are as follows: it can only provide data on one aspect, and the information is not comprehensive; it is impossible to conduct comprehensive analysis of multiple data sources, resulting in insufficient accuracy and reliability of diagnosis; (2) The independent digital twin system uses digital twin technology to model and simulate substation equipment, create a virtual model corresponding to the actual equipment, simulate and monitor the operating status of the equipment, and perform data analysis and fault prediction; The disadvantages of the independent digital twin system are as follows: the independent digital twin system is difficult to obtain and process the dynamic data of the actual equipment in real time; lacks fusion with the actual video data, and cannot conduct comprehensive real-time monitoring and comparison of the equipment; (3) The equipment monitoring system based on image processing installs a single camera in the substation and uses image processing algorithms to analyze the image data of the equipment, detect the status and fault conditions of the equipment, and provide diagnostic information; The disadvantages of the equipment monitoring system based on image processing are as follows: it can only provide data on one aspect, and the information is not comprehensive. A single camera cannot provide a panoramic view and has a limited monitoring range; it is unable to conduct comprehensive analysis of multiple data sources, resulting in insufficient diagnostic accuracy and reliability.

[0004] Therefore, existing technologies usually rely on a single video source or sensor data, and have problems such as limited monitoring scope and results, incomplete information, and inability to predict potential faults. They are unable to meet the needs of comprehensive understanding and accurate diagnosis of the status of substation equipment. Summary of the invention

[0005] In order to overcome the above-mentioned deficiencies of the prior art, the present invention patent application proposes a real-time monitoring and diagnosis method for substation equipment, comprising:

[0006] Collect multiple monitoring video data in the substation in real time, and use video data fusion algorithm to obtain a panoramic view of the substation;

[0007] Collecting the field sensor data of the substation in real time, and using the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, and diagnosing potential faults of the substation;

[0008] Extracting real-time equipment image features of the substation from the panoramic view;

[0009] Based on the real-time device image features and the real-time device simulation data, real-time monitoring of the operation status of the substation equipment is performed;

[0010] Visually presenting the results of the potential fault diagnosis and the results of the real-time monitoring;

[0011] Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

[0012] Preferably, the construction of the improved digital twin model includes:

[0013] According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software;

[0014] The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model;

[0015] Training a deep learning algorithm based on historical fault data of the substation equipment;

[0016] The trained deep learning algorithm is integrated into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model.

[0017] Preferably, the real-time collection of field sensor data of the substation and the use of an improved digital twin model corresponding to the substation to generate real-time device simulation data corresponding to the field sensor data to perform potential fault diagnosis on the substation include:

[0018] Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model;

[0019] Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data;

[0020] Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model.

[0021] Preferably, visually presenting the potential fault diagnosis result and the real-time monitoring result includes:

[0022] When the result of the potential fault diagnosis is that there is a potential fault, the substation equipment with the potential fault is visualized by using an AR device and a fault visualization presentation method;

[0023] Dynamically updating and visualizing the real-time monitoring results through the AR device;

[0024] Among them, the improved digital twin model is integrated on the AR device; the fault visualization presentation method includes color distinction and icon identification distinction.

[0025] Preferably, after performing potential fault diagnosis of substation equipment based on the real-time equipment simulation data through the potential fault diagnosis function of the improved digital twin model, the method further includes:

[0026] When an operator wears the AR device and is located in the substation, the location of the operator in the physical space of the substation is identified by using the scene perception and positioning technology of the AR device;

[0027] The position is used as the current position, and virtual devices corresponding to the surrounding devices of the current position are displayed in the AR device, and when the operator moves, the display of the virtual devices is updated accordingly according to the current position after the movement;

[0028] When it is necessary to operate the improved digital twin model displayed at the current location, interactive operations are performed through the human-computer interaction interface of the AR device according to the interaction requirements.

[0029] Preferably, the real-time collection of multiple monitoring video data in the substation and the use of a video data fusion algorithm to obtain a panoramic view of the substation include:

[0030] Collect multiple monitoring video data in the substation in real time, assign each monitoring video data to a predetermined processing thread for data preprocessing, and obtain the monitoring video data after data preprocessing;

[0031] Based on the monitoring video data after the data preprocessing, a graphics processor is used in combination with an adaptive image fusion algorithm to remove seams and artifacts from overlapping parts of the monitoring video data to generate a panoramic fusion view;

[0032] Using a target detection algorithm to identify the light view in the panoramic fusion view, and adjusting the contrast and clarity of the light view to obtain a panoramic view of the substation;

[0033] The data preprocessing includes at least one or more of the following: monitoring video data decoding, monitoring video data time synchronization and monitoring video data frame processing.

[0034] Preferably, the real-time monitoring of the operation status of substation equipment based on the real-time equipment image features and the real-time equipment simulation data includes:

[0035] Compare the real-time device image features with the real-time device simulation data to monitor whether there are abnormalities in the operation of the device;

[0036] When the operation is abnormal, an early warning signal is sent out by sound or light to notify the operation and maintenance personnel, and a diagnostic report is generated;

[0037] The diagnostic report includes one or more of the following: the operating status of the equipment, the fault type and the cause of the abnormality.

[0038] Based on the same inventive concept, the present patent application also provides a real-time monitoring and diagnosis system for substation equipment, including: a panoramic view generation module, an improved digital twin model application module, an equipment image feature extraction module, an equipment monitoring module and a visualization module;

[0039] The panoramic view generation module is used to collect multiple monitoring video data in the substation in real time, and use a video data fusion algorithm to obtain a panoramic view of the substation;

[0040] The improved digital twin model application module is used to collect the field sensor data of the substation in real time, and use the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, so as to perform potential fault diagnosis on the substation;

[0041] The device image feature extraction module is used to extract the real-time device image features of the substation from the panoramic view;

[0042] The equipment monitoring module is used to monitor the operation status of the substation equipment in real time based on the real-time equipment image features and the real-time equipment simulation data;

[0043] The visualization module is used to visualize the results of the potential fault diagnosis and the results of the real-time monitoring;

[0044] Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

[0045] Preferably, the system further comprises: an improved digital twin model construction module, for:

[0046] According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software;

[0047] The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model;

[0048] Training a deep learning algorithm based on historical fault data of the substation equipment;

[0049] The trained deep learning algorithm is integrated into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model.

[0050] Preferably, the improved digital twin model application module is specifically used for:

[0051] Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model;

[0052] Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data;

[0053] Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model.

[0054] Preferably, the visualization module is specifically used for:

[0055] When the result of the potential fault diagnosis is that there is a potential fault, the substation equipment with the potential fault is visualized by using an AR device and a fault visualization presentation method;

[0056] Dynamically updating and visualizing the real-time monitoring results through the AR device;

[0057] Among them, the improved digital twin model is integrated on the AR device; the fault visualization presentation method includes color distinction and icon identification distinction.

[0058] Preferably, the system further comprises: a human-computer interaction module, which is used to:

[0059] When an operator wears the AR device and is located in the substation, the location of the operator in the physical space of the substation is identified by using the scene perception and positioning technology of the AR device;

[0060] The position is used as the current position, and virtual devices corresponding to the surrounding devices of the current position are displayed in the AR device, and when the operator moves, the display of the virtual devices is updated accordingly according to the current position after the movement;

[0061] When it is necessary to operate the improved digital twin model displayed at the current location, interactive operations are performed through the human-computer interaction interface of the AR device according to the interaction requirements.

[0062] Preferably, the panoramic view generation module is specifically used to:

[0063] Collect multiple monitoring video data in the substation in real time, assign each monitoring video data to a predetermined processing thread for data preprocessing, and obtain the monitoring video data after data preprocessing;

[0064] Based on the monitoring video data after the data preprocessing, a graphics processor is used in combination with an adaptive image fusion algorithm to remove seams and artifacts from overlapping parts of the monitoring video data to generate a panoramic fusion view;

[0065] Using a target detection algorithm to identify the light view in the panoramic fusion view, and adjusting the contrast and clarity of the light view to obtain a panoramic view of the substation;

[0066] The data preprocessing includes at least one or more of the following: monitoring video data decoding, monitoring video data time synchronization and monitoring video data frame processing.

[0067] Preferably, the equipment monitoring module is specifically used for:

[0068] Compare the real-time device image features with the real-time device simulation data to monitor whether there are abnormalities in the operation of the device;

[0069] When the operation is abnormal, an early warning signal is sent out by sound or light to notify the operation and maintenance personnel, and a diagnostic report is generated;

[0070] The diagnostic report includes one or more of the following: the operating status of the equipment, the fault type and the cause of the abnormality.

[0071] Based on the same inventive concept, the patent application of the present invention also provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus;

[0072] The memory is used to store one or more programs;

[0073] When the one or more programs are executed by the at least one processor, a real-time monitoring and diagnosis method for substation equipment as described above is implemented.

[0074] Based on the same inventive concept, the patent application of the present invention also provides a readable storage medium on which a computer program and an execution program are stored. When the execution program is executed, a real-time monitoring and diagnosis method for substation equipment as described above is implemented.

[0075] Compared with the closest prior art, the patent application of this invention has the following beneficial effects:

[0076] The patent application of the present invention provides a method and system for real-time monitoring and diagnosis of substation equipment, including: real-time acquisition of multiple monitoring video data in the substation, and use of a video data fusion algorithm to obtain a panoramic view of the substation; real-time acquisition of field sensor data of the substation, and use of an improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, and perform potential fault diagnosis on the substation; extracting real-time equipment image features of the substation from the panoramic view; based on the real-time equipment image features and the real-time equipment simulation data, real-time monitoring of the operation of the substation equipment; and combining the results of the potential fault diagnosis and the results of the real-time monitoring. Visual presentation; wherein, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation; the panoramic view of the present invention provides detailed image information of the substation, and the real-time equipment image features of the substation can be extracted from the panoramic view. The improved digital twin model can not only synchronize the simulation data of the substation equipment, but also perform potential fault diagnosis, thereby providing early warning. At the same time, by comparing the real-time equipment image features with the synchronized real-time equipment simulation data, comprehensive and accurate real-time monitoring results can be obtained. Therefore, through potential fault diagnosis and real-time monitoring results, it is possible to provide a comprehensive grasp of the status of substation equipment and accurate monitoring and diagnosis needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 A flowchart of a real-time monitoring and diagnosis method for substation equipment provided in the patent application of the present invention;

[0078] Figure 2 A schematic diagram of a real-time monitoring and diagnosis system for substation equipment is provided for the patent application of the present invention;

[0079] Figure 3 A structural schematic diagram of an electronic device is provided for the patent application of the present invention. DETAILED DESCRIPTION

[0080] The specific implementation methods of the patent application of the present invention are further described in detail below in conjunction with the accompanying drawings.

[0081] Embodiment 1:

[0082] The present invention provides a method for real-time monitoring and diagnosis of substation equipment. Figure 1 As shown, including:

[0083] Step 1: Collect multiple monitoring video data in the substation in real time, and use the video data fusion algorithm to obtain a panoramic view of the substation;

[0084] Step 2: Collect the field sensor data of the substation in real time, and use the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, and perform potential fault diagnosis on the substation;

[0085] Step 3: extracting real-time equipment image features of the substation from the panoramic view;

[0086] Step 4: Based on the real-time device image features and the real-time device simulation data, the operation status of the substation equipment is monitored in real time;

[0087] Step 5: Visually present the potential fault diagnosis results and the real-time monitoring results;

[0088] Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

[0089] Before step 1 above, the improved digital twin model needs to be constructed;

[0090] In one implementation, the construction of the improved digital twin model includes:

[0091] According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software;

[0092] For example, use 3D modeling software to model substation equipment and create a virtual 3D model corresponding to the actual equipment, namely the digital twin model; build a digital twin of the substation equipment, and use 3D modeling, simulation and real-time data update to create a virtual 3D model synchronized with the physical equipment; digital twin technology can reflect the operating status and changes of the equipment in real time, providing a dynamic and real-time monitoring platform.

[0093] The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model;

[0094] For example, the digital twin model is simulated based on the current operating data and historical operating data of the device, and device simulation data is generated to reflect the performance of the device under different states.

[0095] Training a deep learning algorithm based on historical fault data of the substation equipment;

[0096] For example, based on machine learning or deep learning algorithms, the fault prediction function is integrated into the digital twin model;

[0097] Integrating the trained deep learning algorithm into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model;

[0098] For example, the present invention simulates the digital twin model under different operating states to generate simulation data under different states. Through this process, the simulation capability of the digital twin model can be improved to ensure the accuracy of the simulation data of the digital twin model during real-time synchronization; the trained deep learning algorithm is integrated into the digital twin model as a potential fault diagnosis function, which provides the digital twin model with a potential fault diagnosis function, and can make correct predictions based on highly accurate simulation data, making real-time monitoring and diagnosis of substation equipment more comprehensive and timely; the present invention creates a digital twin model corresponding to the actual substation equipment and simulates the digital twin model to generate equipment simulation data under different states, which enables the system to perform detailed virtual modeling and state prediction on the equipment, thereby improving the accuracy of monitoring and diagnosis.

[0099] The above step 1 collects multiple monitoring video data in the substation in real time, and uses a video data fusion algorithm to obtain a panoramic view of the substation, including:

[0100] Collect multiple monitoring video data in the substation in real time, assign each monitoring video data to a predetermined processing thread for data preprocessing, and obtain the monitoring video data after data preprocessing;

[0101] For example, traditional video surveillance systems rely on a single or a small number of surveillance cameras to perform fixed-point monitoring of equipment in substations, and operation and maintenance personnel conduct manual patrols and inspections by regularly viewing surveillance videos. The shortcomings of traditional video surveillance systems are as follows: the viewing angle of a single camera is limited, and it is impossible to fully monitor all equipment in the substation; the information between cameras lacks correlation, and it is difficult to form a global view; manual monitoring and diagnosis are required, which is inefficient and prone to omissions or false alarms; the video data fusion algorithm of the present invention fuses the video streams of multiple cameras in real time to generate a complete substation equipment monitoring view, can process the video streams of multiple cameras in real time and generate a seamless monitoring view, and is suitable for the complex environment of substations. The algorithm mainly includes multi-threaded parallel processing, GPU (graphics processing unit) acceleration, adaptive image fusion and delay optimization technologies, which realize fast processing and high-quality fusion of video data. Specifically, the video stream of each camera is assigned to an independent processing thread; each thread is responsible for decoding, synchronizing and preprocessing the video stream of the camera; a thread pool is used to manage multiple threads, and the number of threads is dynamically adjusted to adapt to different loads; the real-time processing of video frames is guaranteed through coordination and synchronization between threads; and multi-threading technology is used to assign the video stream processing tasks of multiple cameras to different processing threads, which significantly improves the efficiency of data processing.

[0102] Based on the monitoring video data after the data preprocessing, a graphics processor is used in combination with an adaptive image fusion algorithm to remove seams and artifacts from overlapping parts of the monitoring video data to generate a panoramic fusion view;

[0103] For example, the parallel computing power of GPU is used to accelerate the processing and fusion of video data, especially in computationally intensive tasks such as feature extraction, image transformation and fusion; an adaptive image fusion algorithm is introduced to process overlapping areas between different cameras, eliminate seams and artifacts, and generate high-quality panoramic views.

[0104] Using a target detection algorithm to identify the light view in the panoramic fusion view, and adjusting the contrast and clarity of the light view to obtain a panoramic view of the substation;

[0105] For example, by optimizing each link in the video processing link, the system delay is reduced and the real-time nature of the video data is ensured; a panoramic view or multi-view display of the device is generated to eliminate the problem of limited viewing angle of a single camera; the advanced image processing and machine learning algorithm YOLO (You Only Look Once, target detection algorithm) algorithm framework is adopted, and a low-light enhancement module is used to improve the contrast and clarity of the image for the substation environment with poor lighting conditions, ensuring that a clear device image can still be obtained in a low-light or high-contrast environment, and the fused video data is efficiently processed and analyzed, which simplifies the processing flow and improves the efficiency and accuracy of monitoring and diagnosis. The processing flow includes synchronization, denoising, distortion correction and perspective fusion; synchronization: time synchronization of video streams of different cameras to ensure the consistency of video data at the same time point; denoising: using a denoising algorithm to remove noise from video data and improve video quality; distortion correction: performing distortion correction on video data to correct image distortion caused by the camera lens; perspective fusion: using an image stitching algorithm (designing a feature point detection and matching algorithm based on the special scene of the substation, adding SURF (Speeded Up Robust Features, feature detection algorithm for image processing, uses the Hessian matrix to detect key points, and uses a Haar wavelet-based descriptor for feature matching. It stitches video frames from different cameras to generate a panoramic view or multi-view display of the equipment; creates a panoramic image covering the entire substation to provide comprehensive equipment status information.

[0106] Wherein, the data preprocessing includes at least one or more of the following: monitoring video data decoding, monitoring video data time synchronization and monitoring video data frame processing; the present invention arranges multiple monitoring cameras in the substation to cover different equipment and areas. These cameras will collect the video stream of the substation equipment in real time, and the video data of each camera will be processed by video fusion through the network to ensure comprehensive and real-time data collection; the equipment monitoring system based on image processing in the prior art has limited viewing angle and complex processing. The present invention generates a panoramic view or multi-view display of the equipment through multi-camera video fusion technology, eliminating the problem of limited viewing angle of a single camera; using advanced image processing and machine learning algorithms, the fused video data is efficiently processed and analyzed, the processing flow is simplified, and the efficiency and accuracy of monitoring and diagnosis are improved; the present invention combines multi-source video data to realize all-round real-time monitoring of substation equipment. Through the video data fusion algorithm, the coverage and accuracy of monitoring can be improved, and more equipment operation status information can be obtained; panoramic view The invention provides detailed image information of the substation, and can extract the real-time equipment image features of the substation from the panoramic view. The invention pre-processes the video data, including synchronization, denoising and distortion correction. These steps ensure the quality and consistency of the video data and provide an accurate data basis for subsequent video fusion and analysis. The multi-camera video data fusion of the invention, by arranging multiple monitoring cameras and using video fusion technology, fuses the perspectives from different cameras to generate a panoramic view or a multi-perspective display. This technology solves the problem of limited perspective of a single camera and realizes comprehensive monitoring of substation equipment. The traditional video monitoring system has limited coverage, isolated information and manual dependence. The invention installs multiple monitoring cameras in the substation and uses video fusion technology to pre-process, synchronize and splice multiple video sources to generate a panoramic view or a multi-perspective display, ensuring comprehensive coverage of all equipment in the substation. In addition, through automated real-time monitoring and diagnosis, the dependence on manual inspections is reduced, and the efficiency and accuracy of monitoring are improved.

[0107] The real-time collection of the field sensor data of the substation in step 2 and the use of the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data and perform potential fault diagnosis on the substation include:

[0108] Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model;

[0109] For example, the data source of the single sensor data monitoring system in the prior art is single, the information is incomplete, and there is a lack of cross-validation. There are a large number of equipment in the substation, such as transformers, circuit breakers, busbars, disconnectors, etc. The structures of these equipment are complex and the operating states are diverse. Traditional monitoring methods are difficult to fully and intuitively display the real-time status of all equipment. The present invention deploys sensors on site to collect temperature, pressure, vibration and other data, and transmits these data to the improved digital twin model in real time. By dynamically updating the improved digital twin model, it is ensured that the content displayed by the subsequent AR device is consistent with the actual device status; the improved digital twin model dynamically updates the virtual status of the equipment, that is, the real-time equipment simulation data, by receiving real-time collected data.

[0110] Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data;

[0111] Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model; the improved digital twin model of the present invention can not only synchronize the simulation data of the substation equipment, but also perform potential fault diagnosis, thereby providing early warning of potential faults.

[0112] The real-time equipment image features described in the above step 3 include: shape features, size features, material features, texture features, position features and direction features; the present invention extracts the real-time equipment image features of the substation for subsequent comparison with the real-time equipment simulation data of the improved digital twin model, and based on the extracted multiple features, a high-accuracy comparison result can be obtained.

[0113] The above step 4, based on the real-time device image features and the real-time device simulation data, performs real-time monitoring on the operation status of the substation equipment, including:

[0114] Compare the real-time device image features with the real-time device simulation data to monitor whether there are abnormalities in the operation of the device;

[0115] When the operation is abnormal, an early warning signal is sent out by sound or light to notify the operation and maintenance personnel, and a diagnostic report is generated;

[0116] The diagnostic report includes one or more of the following: the operating status of the equipment, the fault type and the cause of the abnormality.

[0117] For example, the extracted real-time device image features are compared with the real-time device simulation data generated by the improved digital twin model to identify the actual status of the device; this is equivalent to using image processing and machine learning algorithms to analyze the comparison results and detect whether there are any abnormalities in the equipment. When the operation is abnormal, a detailed diagnostic report is generated to describe the operating status of the equipment, the type of fault and its possible causes. The system automatically sends out an early warning signal and notifies the operation and maintenance personnel through sound, light, etc., so that timely measures can be taken. When performing real-time monitoring, the present invention integrates and analyzes multiple data sources such as video data, sensor data and historical operation data; through the comprehensive processing of multi-source data, the accuracy and reliability of monitoring and diagnosis can be improved, and comprehensive equipment status information can be provided. Information; the present invention combines multiple data sources, including real-time video data and equipment simulation data of the improved digital twin model, and realizes comprehensive monitoring of the equipment status through video fusion and feature extraction technology; by comparing and analyzing the real-time video data with the equipment simulation data of the virtual model, the comprehensiveness and reliability of the data are ensured, and more accurate fault detection and diagnosis are provided; the independent digital twin system in the prior art lacks real-time performance and data fusion. The present invention combines digital twin technology with real-time video fusion technology to realize real-time monitoring and diagnosis of substation equipment; through the synchronous comparison of video data and virtual model, the equipment status and operation status are updated in real time, which ensures the real-time performance of the system and the high efficiency of data fusion, and improves the accuracy of monitoring and diagnosis.

[0118] The step 5 of visually presenting the potential fault diagnosis result and the real-time monitoring result includes:

[0119] When the result of the potential fault diagnosis is that there is a potential fault, the substation equipment with the potential fault is visualized by using an AR (Augmented Reality, augmented reality technology) device and a fault visualization presentation method;

[0120] For example, AR devices are designed with intuitive user interfaces that enable operators to interact with improved digital twin models through gestures, voice, or touch; users can select specific equipment components to view their current status, historical data, and future predictions; AR devices are integrated with improved digital twin models, and when the system predicts a potential failure, the AR device will present warning information in a visual form (such as color changes or icon labels) above the equipment to help operators identify and handle problems in advance.

[0121] Dynamically updating and visualizing the real-time monitoring results through the AR device;

[0122] For example, if there are real-time data changes (such as equipment temperature, pressure, etc.), the AR device will dynamically update the superimposed information to ensure that what the user sees is consistent with the actual equipment status; through real-time collection and processing of video streams and sensor data, real-time monitoring and data updates of substation equipment can be achieved. The AR device can capture the equipment's operating status, fault information, and environmental changes in real time to ensure the real-time and accuracy of the monitoring data, and ensure that the improved digital twin model displayed by AR is consistent with the actual equipment status. By combining the AR device with the improved digital twin model, operators can view the real-time operating status of the equipment on site and intuitively understand the working conditions of the equipment, which helps to quickly locate problems and improve operational efficiency.

[0123] Among them, the improved digital twin model is integrated on the AR device; the fault visualization presentation method includes color distinction and icon identification distinction; the present invention generates a detailed diagnostic report based on the real-time data comparison results, and automatically issues a warning signal when equipment abnormality is detected. This function reduces manual intervention and improves response speed and operation and maintenance efficiency.

[0124] In one implementation, after performing potential fault diagnosis of substation equipment based on the real-time equipment simulation data through the potential fault diagnosis function of the improved digital twin model, the method further includes:

[0125] When an operator wears the AR device and is located in the substation, the location of the operator in the physical space of the substation is identified by using the scene perception and positioning technology of the AR device;

[0126] For example, through the scene perception and positioning functions of AR devices, the physical location of operators can be automatically identified. When operators move in the substation, AR devices can detect their positions in real time and accurately superimpose the corresponding parts of the improved digital twin model on the real equipment, ensuring the consistency of virtual information with the actual equipment. This method allows operators to easily navigate and find specific equipment or components in complex industrial environments, and operators can see virtual information (such as equipment status, operating instructions, etc.) directly superimposed on the actual equipment, thereby ensuring that the virtual display is consistent with the actual equipment.

[0127] AR devices use cameras and sensors to capture images and depth information of the surrounding environment to identify the shape and position of the device; AR devices use GPS (Global Positioning System) to determine the operator's specific position and direction in space, which helps the device understand the user's environment. Once the operator's position is identified, the AR device matches the improved digital twin model with the real device. The system will find the correspondence between the virtual model and the real-world device based on the device's shape, size and other characteristics;

[0128] The position is used as the current position, and virtual devices corresponding to the surrounding devices of the current position are displayed in the AR device, and when the operator moves, the display of the virtual devices is updated accordingly according to the current position after the movement;

[0129] When it is necessary to operate the improved digital twin model displayed at the current location, interactive operations are performed through the human-computer interaction interface of the AR device according to the interaction requirements.

[0130] For example, the virtual operation guidance function can be realized in the AR environment. The operator can use the AR device to simulate the operation steps in the virtual environment and view the real-time feedback of the system to the operation. This function is not only used for guidance in actual operation, but also for the training of new employees, so that they can become familiar with the operation process of the equipment in a safe virtual environment. This is very effective for both actual operation guidance and new employee training.

[0131] AR devices can also provide different levels of data display and visualization options according to the needs and permissions of different operators. For example, maintenance personnel can see the detailed operating parameters of the equipment, while managers can view the overall health status and key performance indicators of the system; AR devices render relevant information of the improved digital twin model through graphics processing, such as equipment status, warning prompts, etc., and present this information on the real-world image through transparent display; design intuitive user interaction interfaces on AR devices so that operators can interact with the improved digital twin model through gestures, voice or touch; users can select specific equipment components through AR devices to view their current operating status, historical data, and future status predictions; intuitive human-computer interaction interfaces provide a comprehensive interface for real-time monitoring, diagnostic results and operation control, so that operation and maintenance personnel can easily view equipment status, operating system settings and adjust monitoring parameters. This enhances the ease of use and user experience of the system.

[0132] The present invention can also realize remote monitoring and operation of substation equipment through network technology. Operators can view the operating status of the equipment in real time through the system interface, perform remote control and operation, reduce on-site workload, and improve work efficiency and safety; the present invention significantly improves the monitoring comprehensiveness and diagnostic accuracy of substation equipment through the combination of video fusion and improved digital twin technology; multi-camera video fusion technology ensures comprehensive coverage of equipment monitoring, and digital twin technology realizes accurate comparison of real-time data with improved digital twin models, timely identifies anomalies and issues early warnings, reduces manual intervention, and improves operation and maintenance efficiency and equipment safety; the present invention compares the real-time data after video fusion processing with the simulation data of the improved digital twin model, and accurately identifies the actual status and potential anomalies of the equipment through feature extraction and data analysis technology. This process uses advanced image processing and machine learning algorithms to improve the accuracy of fault detection; the present invention uses machine learning and artificial intelligence algorithms to analyze real-time monitoring data and historical data, and conducts equipment status evaluation, fault diagnosis and early warning. The intelligent diagnosis system can Identify abnormal conditions in equipment operation, predict potential faults, issue early warning information, and provide decision support; the panoramic view of the present invention provides detailed image information of the substation, and the real-time equipment image features of the substation can be extracted from the panoramic view. The improved digital twin model can not only synchronize the simulation data of the substation equipment, but also perform potential fault diagnosis, and thus can provide early warning for potential faults. At the same time, by comparing the real-time equipment image features with the simulation data of the synchronized substation equipment, comprehensive and accurate real-time monitoring results can be obtained. Therefore, through potential fault prediction and real-time monitoring results, it is possible to provide a comprehensive grasp of the status of substation equipment and accurate diagnosis needs; the present invention comprehensively and intuitively displays the real-time status of all equipment through AR device visualization; through the potential fault diagnosis function, potential fault diagnosis can be performed according to the real-time equipment simulation data, and fault visualization can be performed through AR equipment, which helps to quickly locate problems and improve operating efficiency, and help operators identify and deal with problems in advance.

[0133] Embodiment 2:

[0134] Based on the same inventive concept, the present invention patent application also provides a real-time monitoring and diagnosis system for substation equipment. Figure 2 As shown, it includes: a panoramic view generation module, an improved digital twin model application module, an equipment image feature extraction module, an equipment monitoring module and a visualization module;

[0135] The panoramic view generation module is used to collect multiple monitoring video data in the substation in real time, and use a video data fusion algorithm to obtain a panoramic view of the substation;

[0136] The improved digital twin model application module is used to collect the field sensor data of the substation in real time, and use the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, so as to perform potential fault diagnosis on the substation;

[0137] The device image feature extraction module is used to extract the real-time device image features of the substation from the panoramic view;

[0138] The equipment monitoring module is used to monitor the operation status of the substation equipment in real time based on the real-time equipment image features and the real-time equipment simulation data;

[0139] The visualization module is used to visualize the results of the potential fault diagnosis and the results of the real-time monitoring;

[0140] Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

[0141] Preferably, the system further comprises: an improved digital twin model construction module, for:

[0142] According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software;

[0143] The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model;

[0144] Training a deep learning algorithm based on historical fault data of the substation equipment;

[0145] The trained deep learning algorithm is integrated into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model.

[0146] Preferably, the improved digital twin model application module is specifically used for:

[0147] Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model;

[0148] Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data;

[0149] Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model.

[0150] Preferably, the visualization module is specifically used for:

[0151] When the result of the potential fault diagnosis is that there is a potential fault, the substation equipment with the potential fault is visualized by using an AR device and a fault visualization presentation method;

[0152] Dynamically updating and visualizing the real-time monitoring results through the AR device;

[0153] Among them, the improved digital twin model is integrated on the AR device; the fault visualization presentation method includes color distinction and icon identification distinction.

[0154] Preferably, the system further comprises: a human-computer interaction module, which is used to:

[0155] When an operator wears the AR device and is located in the substation, the location of the operator in the physical space of the substation is identified by using the scene perception and positioning technology of the AR device;

[0156] The position is used as the current position, and virtual devices corresponding to the surrounding devices of the current position are displayed in the AR device, and when the operator moves, the display of the virtual devices is updated accordingly according to the current position after the movement;

[0157] When it is necessary to operate the improved digital twin model displayed at the current location, interactive operations are performed through the human-computer interaction interface of the AR device according to the interaction requirements.

[0158] Preferably, the panoramic view generation module is specifically used to:

[0159] Collect multiple monitoring video data in the substation in real time, assign each monitoring video data to a predetermined processing thread for data preprocessing, and obtain the monitoring video data after data preprocessing;

[0160] Based on the monitoring video data after the data preprocessing, a graphics processor is used in combination with an adaptive image fusion algorithm to remove seams and artifacts from overlapping parts of the monitoring video data to generate a panoramic fusion view;

[0161] Using a target detection algorithm to identify the light view in the panoramic fusion view, and adjusting the contrast and clarity of the light view to obtain a panoramic view of the substation;

[0162] The data preprocessing includes at least one or more of the following: monitoring video data decoding, monitoring video data time synchronization and monitoring video data frame processing.

[0163] Preferably, the equipment monitoring module is specifically used for:

[0164] Compare the real-time device image features with the real-time device simulation data to monitor whether there are abnormalities in the operation of the device;

[0165] When the operation is abnormal, an early warning signal is sent out by sound or light to notify the operation and maintenance personnel, and a diagnostic report is generated;

[0166] The diagnostic report includes one or more of the following: the operating status of the equipment, the fault type and the cause of the abnormality.

[0167] Example 3

[0168] like Figure 3 As shown, the present invention also provides an electronic device, which may be a computer device, a single-chip device, an intelligent mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, the processor, and the transceiver component are connected via a bus; the memory may be used to store an execution program, and an exemplary execution program may include instructions; the processor is used to execute the instructions stored in the memory. The memory may also be used to store data, which may be called and / or modified when the instructions are executed.

[0169] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in a storage medium to implement the corresponding method flow or corresponding functions, so as to realize the steps of a real-time monitoring and diagnosis method for substation equipment in the above-mentioned embodiment.

[0170] Example 4

[0171] Based on the same inventive concept, the present invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory), which is a memory device in an electronic device for storing programs and data. It can be understood that the storage medium here can include both built-in storage media in electronic devices and, of course, extended storage media supported by electronic devices. The storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more execution programs (including program codes). It should be noted that the storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor loads and executes one or more instructions stored in the storage medium, which can implement the steps of a real-time monitoring and diagnosis method for substation equipment in the above embodiment.

[0172] It should be understood by those skilled in the art that the embodiments of the present invention patent application can be provided as methods, systems, or computer program products. Therefore, the present invention patent application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention patent application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0173] The present invention patent application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present invention patent application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0174] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0175] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the patent application of the present invention rather than to limit its protection scope. Although the patent application of the present invention is described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the patent application of the present invention, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, but these changes, modifications or equivalent substitutions are all within the protection scope of the claims to be approved.

Claims

1. A real-time monitoring and diagnosis method for substation equipment, characterized in that: include: Collect multiple monitoring video data in the substation in real time, and use video data fusion algorithm to obtain a panoramic view of the substation; Collecting the field sensor data of the substation in real time, and using the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, and diagnosing potential faults of the substation; Extracting real-time equipment image features of the substation from the panoramic view; Based on the real-time device image features and the real-time device simulation data, real-time monitoring of the operation status of the substation equipment is performed; Visually presenting the results of the potential fault diagnosis and the results of the real-time monitoring; Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

2. The method according to claim 1, characterized in that The construction of the improved digital twin model includes: According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software; The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model; Training a deep learning algorithm based on historical fault data of the substation equipment; The trained deep learning algorithm is integrated into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model.

3. The method according to claim 1 or 2, characterized in that The real-time collection of the field sensor data of the substation and the use of the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data and perform potential fault diagnosis on the substation include: Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model; Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data; Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model.

4. The method according to claim 1, characterized in that The visual presentation of the potential fault diagnosis result and the real-time monitoring result includes: When the result of the potential fault diagnosis is that there is a potential fault, the substation equipment with the potential fault is visualized by using an AR device and a fault visualization presentation method; Dynamically updating and visualizing the real-time monitoring results through the AR device; Among them, the improved digital twin model is integrated on the AR device; the fault visualization presentation method includes color distinction and icon identification distinction.

5. The method according to claim 4, characterized in that After performing potential fault diagnosis of substation equipment based on the real-time equipment simulation data through the potential fault diagnosis function of the improved digital twin model, the method further includes: When an operator wears the AR device and is located in the substation, the location of the operator in the physical space of the substation is identified by using the scene perception and positioning technology of the AR device; The position is used as the current position, and virtual devices corresponding to the surrounding devices of the current position are displayed in the AR device, and when the operator moves, the display of the virtual devices is updated accordingly according to the current position after the movement; When it is necessary to operate the improved digital twin model displayed at the current location, interactive operations are performed through the human-computer interaction interface of the AR device according to the interaction requirements.

6. The method according to claim 1, characterized in that The real-time collection of multiple monitoring video data in the substation and the use of a video data fusion algorithm to obtain a panoramic view of the substation include: Collect multiple monitoring video data in the substation in real time, assign each monitoring video data to a predetermined processing thread for data preprocessing, and obtain the monitoring video data after data preprocessing; Based on the monitoring video data after the data preprocessing, a graphics processor is used in combination with an adaptive image fusion algorithm to remove seams and artifacts from overlapping parts of the monitoring video data to generate a panoramic fusion view; Using a target detection algorithm to identify the light view in the panoramic fusion view, and adjusting the contrast and clarity of the light view to obtain a panoramic view of the substation; The data preprocessing includes at least one or more of the following: monitoring video data decoding, monitoring video data time synchronization and monitoring video data frame processing.

7. The method according to claim 1, characterized in that The real-time monitoring of the operation status of the substation equipment based on the real-time equipment image features and the real-time equipment simulation data includes: Compare the real-time device image features with the real-time device simulation data to monitor whether there are abnormalities in the operation of the device; When the operation is abnormal, an early warning signal is sent out by sound or light to notify the operation and maintenance personnel, and a diagnostic report is generated; The diagnostic report includes one or more of the following: the operating status of the equipment, the fault type and the cause of the abnormality.

8. A real-time monitoring and diagnosis system for substation equipment, characterized in that: include: Panoramic view generation module, improved digital twin model application module, equipment image feature extraction module, equipment monitoring module and visualization module; The panoramic view generation module is used to collect multiple monitoring video data in the substation in real time, and use a video data fusion algorithm to obtain a panoramic view of the substation; The improved digital twin model application module is used to collect the field sensor data of the substation in real time, and use the improved digital twin model corresponding to the substation to generate real-time equipment simulation data corresponding to the field sensor data, so as to perform potential fault diagnosis on the substation; The device image feature extraction module is used to extract the real-time device image features of the substation from the panoramic view; The equipment monitoring module is used to monitor the operation status of the substation equipment in real time based on the real-time equipment image features and the real-time equipment simulation data; The visualization module is used to visualize the results of the potential fault diagnosis and the results of the real-time monitoring; Among them, the improved digital twin model is obtained by integrating a deep learning algorithm with potential fault diagnosis into the digital twin model corresponding to the substation.

9. The system according to claim 8, characterized in that The system also includes: a building module of an improved digital twin model, for: According to the structural relationship of substation equipment, a digital twin model of the substation is constructed using 3D modeling software; The digital twin model is simulated using the historical operating data of the substation equipment under different operating states, and the equipment simulation data of the digital twin model under different operating states is trained to obtain the simulated digital twin model; Training a deep learning algorithm based on historical fault data of the substation equipment; The trained deep learning algorithm is integrated into the simulated digital twin model as a potential fault diagnosis function to complete the construction of the improved digital twin model.

10. The system according to claim 8 or 9, characterized in that The improved digital twin model application module is specifically used for: Synchronizing the real-time collected data of the field sensors in the substation into the improved digital twin model; Dynamically updating the real-time device simulation data in the improved digital twin model according to the real-time collected data; Based on the real-time equipment simulation data, potential fault diagnosis of substation equipment is performed through the potential fault diagnosis function of the improved digital twin model.

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