An integrated engine system and processing method based on distributed artificial intelligence

Abstract

An integrated engine system based on distributed artificial intelligence and its processing method. The method includes taking images of each device and collecting the operation data of all devices in the power station, marking them in a semi-automatic image annotation manner, comprehensively analyzing and processing the marked images of each device in the power station and the device operation data, and performing model modeling and model training; realizing operation monitoring and comprehensive display of the operation information, protection information, and operation status of the power station through a visualization method. The above method can achieve the integration of collection, marking, training, recognition, etc., can identify and inspect the operation conditions of devices and environmental security, timely discover and solve potential hidden dangers, prevent power equipment failure problems, and improve the device status perception, defect discovery active early warning, and risk control capabilities of substation operation and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of information processing and the technical field of intelligent substations, and particularly relates to an integrated engine system and a processing method based on distributed artificial intelligence. Background Art

[0002] As an important carrier of electric power, the power grid plays a role in ensuring power supply safety and can promote the achievement of the "dual carbon" goal. However, with the rapid development of power grid construction, the number of substations has increased rapidly. Under the current monitoring and management mode of substation equipment, problems such as the contradiction between equipment monitoring intensification and lean management, the lack of effective monitoring means for operation and maintenance personnel, and the weakening of equipment operation and maintenance capabilities have become increasingly prominent.

[0003] Currently, the main drawbacks of power grid inspection in substations are as follows:

[0004] (1) When inspecting, the inspectors need to carry a variety of equipment, which occupies both hands and affects the inspection efficiency;

[0005] (2) When problems are found on site, the communication methods for problem feedback are limited, and at the same time, the in-station personnel cannot understand the status of the inspectors in real time;

[0006] (3) Since traditional substations require manual regular inspections, missed inspections and misinspections occur frequently, resulting in the inspection results being less intuitive and visual, and the inspection process being difficult to trace, thus unable to guarantee the accuracy of the inspection results.

[0007] In addition, although the regular equipment and environment inspections in substations play a certain role in preventing equipment failures and accidents, they lack the timeliness of inspection information. Therefore, this conservative inspection mode is no longer suitable for modern management requirements and has obvious deficiencies and drawbacks. Summary of the Invention

[0008] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an integrated engine system and a processing method based on distributed artificial intelligence, which can realize the integration of collection, marking, training, recognition, etc., can identify and inspect the operation status of equipment and environmental security, timely discover and solve potential hidden dangers, prevent power equipment failure problems, and improve the equipment status perception, defect discovery and active warning, and risk control capabilities of substation operation and maintenance.

[0009] The present invention provides an integrated engine processing method based on distributed artificial intelligence, including the following steps carried out in sequence:

[0010] (1) Using a camera device with a non-single straight-line track walking method, controlling the camera device to take images of each device from multiple angles within the shooting range covering all the devices in the power station; at the same time, collecting the operation data of all the devices in the power station;

[0011] (2) Adopt a semi-automatic image annotation method to mark the images of each device in a form that fits the actual state of the power station, and send the marked image samples into the model training library;

[0012] (3) Comprehensively analyze and process the marked images of each device in the power station and the device operation data, and perform model modeling and model training based on the processing results;

[0013] (4) Realize the operation monitoring and comprehensive display of the operation information, protection information, and operation status of the power station through a visualization method.

[0014] Among them, in the step (1), the shooting angle range of the control camera device is greater than the angle range covering all the devices in the intelligent power station.

[0015] Among them, all the devices in the intelligent power station covered in the step (1) include at least one of high-voltage power distribution equipment, low-voltage power distribution equipment, rectification equipment, and switching power supplies.

[0016] Among them, in the step (1), collect the operation data of all the devices in the substation, specifically, perform real-time collection of at least one of current, voltage, power, frequency data, and fault information respectively.

[0017] Among them, in the step (3), comprehensively analyze and process the marked images of each device in the intelligent substation and the device operation data, specifically, perform data processing, data storage, and data resource management.

[0018] Among them, in the step (3), perform model modeling and model training, specifically: link the model training library with the production system. After the production system determines an identification error, the determination result of this item is automatically added to the model training library, and the training process is started.

[0019] Among them, the model training process is specifically: classify the images in the model training library according to the scale of the substation, voltage level, and wiring method, and intelligently select the device defect photos close to the substation classification for classification learning.

[0020] Among them, during the process of model modeling and model training, the ANSYS simulation software is also used to simulate at least one of the device stress, magnetic field, and temperature field to generate more pictures for specific model training.

[0021] Among them, based on the image recognition technology of OpenCV, automatically correct the results of the machine learning algorithm.

[0022] The present invention also provides an integrated engine system based on distributed artificial intelligence, which is used to implement the integrated engine processing method based on distributed artificial intelligence. The system includes:

[0023] The business layer, which includes a video sampling data module and a device data module; among them, the video sampling data module is used to control a camera device with a non-single straight-line track walking mode to take images of each device from multiple angles within the shooting range covering all devices in the intelligent power station; the device data module is used to collect the operation data of all devices in the substation;

[0024] The artificial intelligence layer is used to comprehensively analyze and process the marked images of each device in the power station and the device operation data, and perform model modeling and model training based on the processing results;

[0025] The business layer is used to realize the operation monitoring and comprehensive display of the operation information, protection information, and operation status of the power station in a visual manner.

[0026] The integrated engine system and processing method based on distributed artificial intelligence can achieve:

[0027] (1) Provide the on-line intelligent inspection function for the substation, making it have higher management and inspection efficiency, realizing the lean management, lean detection, and lean control of substation equipment, bringing low cost, visualization, and high efficiency to the power industry, and realizing the unmanned, digital, and intelligent inspection of the substation;

[0028] (2) By integrating the engine system into the intelligent operation and maintenance inspection system, centralized monitoring of power station equipment and equipment algorithm training, automatically diagnose and intelligently warn the equipment status, abnormal environment, and operation behavior in the substation, improve the state perception and control ability of substation equipment, realize the identification and inspection of the equipment operation situation and environmental security and protection, timely discover and solve potential hidden dangers, prevent power equipment failure problems, and enhance the equipment state perception, defect discovery, active warning, and risk control ability of substation operation and maintenance;

[0029] (3) Through multi-angle shooting by the camera, increase the abnormal device recognition range; through semi-automatic annotation of the collected device images, improve the feasibility of safe operation and maintenance; through device model training, greatly improve the fault recognition efficiency; through simulation, provide a large number of training materials, enrich the model types, and ensure the accuracy of data processing. Effectively reduce the pressure on operation and maintenance personnel, realize the unmanned control of the substation, accelerate the pace of substation intelligence, help the substation achieve safe production supervision, reduce the fault power outage time, and ensure the stable power supply and safe operation of the power grid;

[0030] (4) The integrated system of "platform + artificial intelligence" is used to deal with the increasingly complex substation equipment, improve the efficiency of environmental security management inspection, bring a more orderly production environment and inspection and maintenance results to the power industry, and has a high performance-price ratio;

[0031] (5) Simple means, easy collection of device information, system deployment and operation; Device standardization: Through standardized interfaces, communication protocols, the system is modularized, facilitating later system expansion and upgrade; Short construction time: The system installation and commissioning can be completed in a short time; Easy maintenance: Modular structure and with expert self-diagnosis function, easy for operation and maintenance management; Low investment: High performance-price ratio, reducing costs. Brief Description of the Drawings

[0032] Figure 1 It is a schematic structural diagram of an integrated engine system based on distributed artificial intelligence. Detailed Implementation Modes

[0033] The following details the specific implementation of the present invention. It is necessary to point out here that the following implementation is only for further illustration of the present invention and cannot be construed as a limitation on the protection scope of the present invention. Some non-essential improvements and adjustments made by those skilled in the art to the present invention based on the above content of the present invention still fall within the protection scope of the present invention.

[0034] The present invention provides an integrated engine system based on distributed artificial intelligence, and its specific implementation is as shown in the attached Figure 1 figure, where Figure 1 is a schematic structural diagram of an integrated engine system based on distributed artificial intelligence. The following specifically introduces the parking accuracy processing method of the train autonomous operation system.

[0035] The present invention provides an integrated engine system based on distributed artificial intelligence, which is an integrated engine system applicable to intelligent substations, applicable to intelligent operation and maintenance of intelligent power stations, helps the power grid operate stably, and improves operation and maintenance efficiency.

[0036] The integrated engine system based on distributed artificial intelligence is integrated into the intelligent operation and maintenance inspection system, and continuously optimizes the work of the four main parts of acquisition, marking, training, and recognition respectively. Among them, the integrated system mainly completes the four main tasks of device image sample acquisition, image marking, model training, and image recognition. The intelligent operation and maintenance inspection system is mainly responsible for the unified management and unified deployment of models, and realizes the management and application of models of different manufacturers and different framework types.

[0037] The four main steps mainly executed by the integrated engine processing method based on artificial intelligence:

[0038] (1) Image acquisition: By improving the single straight-line walking mode of the camera track and increasing the rotation angle of the camera, it is convenient for the camera to take pictures of each device from multiple angles, enabling all devices in the intelligent power station to be included in the model, greatly increasing the recognition range of electrical equipment abnormalities and reducing the recognition time. Through the above method, real-time, efficient, and comprehensive data collection of current, voltage, power, and frequency can be carried out for all devices such as high-voltage power distribution, low-voltage power distribution, rectification equipment, and switching power supplies in the intelligent power station in all directions, greatly increasing the operation and maintenance duration and operation and maintenance efficiency.

[0039] (2) Image marking: The integrated system is integrated into the intelligent operation and maintenance patrol system and uses semi-automatic image annotation technology to semi-automatically annotate the images of all devices in the intelligent power station, thus avoiding the trouble of mutual copying of image data caused by the independence of the annotation tool and the patrol system, assisting in annotation, improving the annotation recognition efficiency, and effectively shortening the image acquisition duration. By providing high-performance, highly reliable (millisecond-level response), one-stop operation and maintenance data services, all device image information is accessed in real time and efficiently based on semi-automatic image annotation technology, realizing low-cost storage, efficient calculation, and fast marking recognition.

[0040] (3) Model training: The model management database is linked with the production system. After the production system determines an identification error, the determination result is automatically added to the model training database, thus starting model training. In model training management, the images in the training library are classified according to the substation scale, voltage level, and wiring method, helping the operation and maintenance patrol system of this substation to intelligently select the equipment defect photos of substations with a classification close to this station for classification learning, improving the recognition effect, and enhancing the data utilization rate. By linking the model training database with the production system, a large number of algorithm libraries can be quickly constructed for the intelligent power station to generate high-precision models. In subsequent model training, the defects brought by each device during the inspection process can be solved one by one, thus greatly reducing the operation and maintenance cost and improving the operation and maintenance patrol efficiency.

[0041] (4) Image recognition: Simulation software such as ANSYS is used to simulate the force, magnetic field, temperature field, etc. of the device to generate more pictures for specific model training. Based on image recognition technology similar to OpenCV, the results of machine learning algorithms are automatically corrected to provide more training materials, realizing a virtuous cycle of "model learning → detection → model enrichment → more accurate detection → more enriched model → more accurate detection". Simulation software similar to ANSYS is used to help accurately simulate the reasonable values of various parameters such as the force, magnetic field, and temperature field of the device at each stage based on its powerful background processing function; image recognition technology similar to OpenCV is used to automatically correct the results of machine learning algorithms, providing a rich and accurate training library for model training and effectively improving the system's recognition ability.

[0042] The present invention provides an integrated engine system based on distributed artificial intelligence. The integrated engine system integrates an intelligent power station operation and maintenance patrol system to achieve real-time monitoring of equipment, timely grasp the operation data of the equipment, and detect equipment operation failures. For equipment failures, rapid analysis and processing can be carried out, which can be efficient, accurate, and visual, improving the operation and maintenance efficiency and ensuring power generation. It realizes the informatization, standardization, and normalization of work, and ensures the safe and reliable operation of the substation. The integrated system analyzes the production operation data of the power station, provides comprehensive model training, and conducts vertical comparison of a single power station and horizontal comparison of multiple power stations in multiple aspects such as power generation and operation and maintenance, so as to discover the deficiencies of the power station, continuously optimize, and ensure the safe and stable operation of the power station.

[0043] In the specific implementation process, the integrated engine system based on distributed artificial intelligence mainly includes three parts, namely the device layer, the artificial intelligence layer, and the service layer:

[0044] The device layer is used for data acquisition of the device layer. The device layer includes a device data module and a video sampling data module. Among them, the substation device data module is used to collect the operation data of all substation devices, including voltage, fault information, etc.; the video sampling data module is used to collect all device video image information, so as to provide materials for sample recognition marking and model training management. Specifically, in the device layer, standard interfaces and information interaction are used to realize the monitoring and control of auxiliary devices such as in-station power supplies and videos. When taking images of electrical equipment, by adopting a non-linear walking method, the rotation angle of the camera pair is adjusted to obtain multi-angle and all-round images, and corresponding image information can be obtained, expanding the scope of identifying electrical equipment abnormalities. After obtaining the images, through the semi-automatic image annotation method, the images of the current device are directly annotated, which fits the actual state of the station, and each recognized image sample is directly sent to the model training library for model learning. Such a processing method can avoid the mutual copying of image data, reduce data errors, effectively improve the accuracy of image recognition and annotation, improve the recognition efficiency, greatly reduce the annotation workload, and reduce the operation and maintenance pressure.

[0045] The artificial intelligence layer provides classification modeling, classification alerts, fault reports, etc. by comprehensively analyzing and processing the operation images of various devices in the intelligent substation, thereby improving the operation and maintenance efficiency. The artificial intelligence layer includes a data center and a model center. Among them, the data center is used for data processing, data storage, and data resource management; the model center is used for sample recognition, marking, model training, and model simulation. At the same time, the model center is also responsible for the unified management and deployment of models. Specifically, in the intelligent power station modeling, the model management database is linked with the production system. After the production system determines an identification error, the determination result will be automatically added to the model training library, and the training process will be started to enrich the training library. After the training is started, the images in the training library are classified according to the substation scale, voltage level, and wiring method, and the equipment defect photos of substations similar to the classification of this station are intelligently selected for classification learning, greatly improving the recognition effect. At the same time, simulation software such as ANASYS is used to conduct simulation analysis by combining multiple physical fields, and simulation analysis is carried out on equipment stress, magnetic field, temperature field, etc.; similar to OpenCV image recognition technology, from "edge detection → contour detection", and various transformation methods are relied on to automatically correct the results of machine learning algorithms, so as to provide richer and more accurate picture materials, enrich the training library, and facilitate model training and learning.

[0046] The business layer realizes the operation monitoring and comprehensive display of power station operation information, protection information, operation status, etc. through visualization technology. The business layer includes a substation inspection module and a on-site safety operation module. Among them, the substation inspection module is equipped with an intelligent power station inspection system of an integrated engine system, which is used for regular inspections to ensure the stable operation of the site and realize the visual operation monitoring of the intelligent power station at the business layer.

[0047] The integrated engine system and processing method based on distributed artificial intelligence provided by the present invention can assist the operation and maintenance management of intelligent power stations:

[0048] (1) Compared with the traditional regular inspection methods such as daily, weekly, and monthly inspections, through 24-hour * 365-day automated inspections, the inspection duration and efficiency are more than a hundred times that of the conventional methods;

[0049] (2) Real-time inspection of the image information of the electric energy, active and reactive power, current and voltage, switch status, etc. of all devices in the substation, whether there is a leakage situation, the leakage situation, dust value, temperature and humidity, ozone, SF6, O2, etc. changes in the current natural environment, and diagnose the operation status of environmental adjustment devices such as fans, humidifying devices, and air conditioners. Through model learning, classification modeling is carried out according to the device type, and the image information related to this type of this station is intelligently screened to improve the recognition effect;

[0050] (3)Supported by technologies such as communication and databases, it automatically uploads inspection image information, stores it in a timely manner, and facilitates maintenance personnel to print and query inspection information at any time. It has characteristics such as higher authenticity, accuracy, efficiency, visualization, and security.

[0051] (4)Based on the image information, with semi-automatic image recognition technology, it semi-automatically annotates the collected images, analyzes whether the dynamic values of power equipment and the natural environment are in a faulty or abnormal state, and can notify relevant personnel at the fastest speed. For example, when it detects an abnormal current temperature value, it automatically activates the sound and light equipment and makes a phone call for fire alarm notification.

[0052] (5)It is designed to help the intelligent substation inspection system cope with the increasingly complex substation equipment, effectively improve the inspection efficiency of environmental security management, and can bring low-cost, visualized, and more orderly inspection and maintenance results for power equipment and the natural environment in the power industry.

[0053] The integrated engine system and processing method based on distributed artificial intelligence provided by the present invention, on the basis of improving the construction of the sample library, helps the substation to achieve sample extraction, sample annotation, and full-life-cycle sample management by specialty and type. And on this basis, it completes the unified standardization of power data, supports the construction of the substation sample library and the overall sharing of the sample library resources of the headquarters of the State Grid. By providing machine learning and deep learning development capabilities, it makes the intelligent operation and maintenance inspection system more perfect, with a variety of high-quality algorithms built-in, realizing the closed-loop of model training, evaluation, and optimization. At the same time, the integrated engine system and processing method based on distributed artificial intelligence provide a variety of modeling methods, effectively improving the cultivation of intelligent power station talent teams and the research ability of artificial intelligence technology, providing general and personalized artificial intelligence services, and helping business systems to improve intelligence accurately. It realizes the unified management of edge devices, the unified distribution of artificial intelligence capabilities, and improves the real-time performance and accuracy of edge computing capabilities. After the completion of the present invention, it will build an ecological chain of "platform + service", support diverse intelligent scenarios, and promote the intelligent upgrade of power.

[0054] In the case of an increasing number of substation video monitoring devices and increasingly refined operation and maintenance management, the integrated engine system provided by the present invention is integrated into the intelligent operation and maintenance inspection system, which can automatically diagnose and intelligently warn the equipment status, abnormal environment, and operation behavior in the substation, improve the state perception and control ability of substation equipment, and thus realize intelligent inspection of the substation. Combining the results of targeted model training, functions such as automatic inspection, automatic recognition, intelligent warning, and intelligent decision-making ensure the safe and stable operation of power station equipment, facilitate operation and maintenance personnel to quickly master the operation and maintenance conditions of front-end equipment, and effectively reduce the labor intensity and operation risks of operation and maintenance personnel.

[0055] Next, a method for processing an integrated engine based on distributed artificial intelligence will be specifically introduced, which includes the following steps carried out in sequence:

[0056] (1) Use a camera device with a non-single straight-line track walking method to control the camera device to take images of each device from multiple angles within the shooting range covering all the devices in the power station; at the same time, collect the operation data of all the devices in the power station. Among them, the shooting angle range of the camera device is controlled to be greater than the angle range covering all the devices in the intelligent power station. Covering all the devices in the intelligent power station includes at least one of high-voltage power distribution equipment, low-voltage power distribution equipment, rectification equipment, and switching power supply. The operation data of all the devices in the substation is collected, specifically, at least one of current, voltage, power, frequency data, and fault information is collected in real time

[0057] (2) Adopt a semi-automatic image annotation method to mark the images of each device in a form that conforms to the actual state of the power station, and send the marked image samples to the model training library;

[0058] (3) Conduct comprehensive analysis and processing on the marked images and device operation data of each device in the power station, and perform model modeling and model training based on the processing results. Among them, for the marked images and device operation data of each device in the intelligent substation, comprehensive analysis and processing are specifically carried out for data processing, data storage, and data resource management. Among them, for model modeling and model training, specifically: link the model training library with the production system. After the production system determines an identification error, the determination result of this item is automatically added to the model training library, and the training process is started. Among them, the model training process is specifically: classify the images in the model training library according to the scale of the substation, voltage level, and wiring method, and intelligently select device defect photos close to the substation classification for classification learning. During the process of model modeling and model training, ANSYS simulation software is also used to simulate at least one of device stress, magnetic field, and temperature field to generate more pictures for specific model training. Based on the image recognition technology of OpenCV, the results of machine learning algorithms are automatically corrected

[0059] (4) Realize the operation monitoring and comprehensive display of the operation information, protection information, and operation status of the power station through a visual method.

[0060] The integrated engine processing method based on distributed artificial intelligence provided by the present invention can be processed in a computer device. The processing device can be a computer device that executes the above method. The computer device can include one or more processors, such as one or more central processing units (CPUs), and each processing unit can implement one or more hardware threads. The computer device can also include any memory for storing any kind of information such as code, settings, data, etc. Non-limiting examples include any one or a combination of the following: any type of RAM, any type of ROM, flash devices, hard disks, optical discs, etc. More generally, any memory can store information using any technology. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory can represent a fixed or removable component of the computer device. In one case, when the processor executes the associated instructions stored in any memory or combination of memories, the computer device can perform any operation of the associated instructions. The computer device also includes one or more drive mechanisms for interacting with any memory, such as a hard disk drive mechanism, an optical disc drive mechanism, etc.

[0061] The computer device can also include an input / output module (I / O) for receiving various inputs (via input devices) and for providing various outputs (via output devices). A specific output mechanism can include a presentation device and an associated graphical user interface (GUI). In other embodiments, the input / output module (I / O), input devices, and output devices may not be included and the computer device only serves as a computer device in a network. The computer device can also include one or more network interfaces for exchanging data with other devices via one or more communication links. One or more communication buses couple the components described above together.

[0062] The communication link can be implemented in any way, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link can include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0063] Although, for purposes of illustration, exemplary embodiments of the present invention have been described, those skilled in the art will understand that various changes in form and detail, such as modifications, additions, and substitutions, can be made without departing from the scope and spirit of the invention disclosed in the appended claims. All such changes should fall within the scope of the appended claims of the present invention, and each part of the product and each step in the method claimed by the present invention can be combined together in any combination. Therefore, the description of the embodiments disclosed in the present invention is not intended to limit the scope of the present invention, but to describe the present invention. Accordingly, the scope of the present invention is not limited by the above embodiments, but is defined by the claims or their equivalents.

Claims

1. An integrated engine processing method based on distributed artificial intelligence, characterized in that, it includes the following steps carried out in sequence: (1) Using a camera device with a non-single straight-line track walking mode, controlling the camera device to take images of each device from multiple angles within the shooting range covering all the devices in the power station; meanwhile, collecting the operation data of all the devices in the power station; (2) Adopting a semi-automatic image annotation method to mark the images of each device in a form that fits the actual state of the power station, and sending the marked image samples into the model training library; (3) Conducting comprehensive analysis and processing on the marked images of each device in the power station and the device operation data, and carrying out model modeling and model training based on the processing results; Among them, conducting comprehensive analysis and processing on the marked images of each device in the intelligent substation and the device operation data specifically means conducting data processing, data storage and data resource management; Among them, carrying out model modeling and model training specifically means: linking the model training library with the production system, after the production system determines an identification error, automatically adding this determination result to the model training library and starting the training process; Among them, the model training process specifically means: classifying the images in the model training library according to the substation scale, voltage level, and wiring method, and intelligently selecting device defect photos close to the substation classification for classification learning; Among them, during the process of carrying out model modeling and model training, the ANSYS simulation software is also used to simulate at least one of the device stress, magnetic field, and temperature field to generate more pictures for specific model training; Among them, based on the image recognition technology of OpenCV, automatically correcting the results of the machine learning algorithm; (4) Realizing the operation monitoring and comprehensive display of the operation information, protection information, and operation status of the power station through a visual method.

2. The method according to claim 1, characterized in that: In the step (1), the shooting angle range of the controlled camera device is greater than the angle range covering all the devices in the intelligent power station.

3. The method according to claim 1 or 2, characterized in that: All the devices included in the intelligent power station in the step (1) include at least one of high-voltage power distribution equipment, low-voltage power distribution equipment, rectification equipment, and switching power supplies.

4. The method according to claim 3, characterized in that: In the step (1), collecting the operation data of all the devices in the substation specifically means respectively carrying out real-time collection of at least one of current, voltage, power, frequency data, and fault information.

5. An integrated engine system based on distributed artificial intelligence, which is used to implement the integrated engine processing method based on distributed artificial intelligence according to any one of claims 1-4, the system includes: The service layer, which includes a video sampling data module and a device data module; Among them, the video sampling data module is used to use a camera device with a non-single straight-line track walking mode to control the camera device to take images of each device from multiple angles within the shooting range covering all the devices in the intelligent power station; the device data module is used to collect the operation data of all the devices in the substation; The artificial intelligence layer is used to comprehensively analyze and process the images marked with each device in the power station and the device operation data, and perform model building and model training based on the processing results; The business layer is used to realize the operation monitoring and comprehensive display of the operation information, protection information and operation status of the power station in a visual way.

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