Substation equipment operation and maintenance diagnosis system

Abstract

The invention provides a substation equipment operation and maintenance diagnosis system, and relates to the technical field of substation diagnosis. The system realizes real-time monitoring and efficient operation and maintenance of substation equipment through integrating a plurality of functional modules such as data acquisition, fault diagnosis, early warning prompt, operation and maintenance management and the like. The system can acquire operation data of equipment in real time, and performs automatic fault identification and positioning through an advanced algorithm model. Once the equipment is diagnosed to have a fault or a potential risk, the system immediately triggers the early warning prompt module to send early warning information to operation and maintenance personnel so as to take measures in time. The substation equipment operation and maintenance diagnosis system has the advantages of being accurate in diagnosis, timely in early warning, efficient in operation and maintenance and the like, the operation and maintenance efficiency and reliability of substation equipment can be greatly improved, the operation and maintenance cost is reduced, and powerful guarantee is provided for development of the power industry.

Description

Technical Field

[0001] The present invention relates to the technical field of substation diagnosis, and in particular to a substation equipment operation and maintenance diagnosis system. Background Art

[0002] With the rapid development of the power industry, the scale and complexity of substation equipment are increasing, and the operation and maintenance of equipment has become the key to ensure the safe and stable operation of the power grid. Traditional operation and maintenance methods mainly rely on manual inspections and experience judgment, which are inefficient and prone to errors. Therefore, the development of a system that can automatically diagnose equipment failures, provide early warnings, and manage operation and maintenance is of great significance to improving the operation and maintenance efficiency and reliability of substation equipment. Summary of the invention

[0003] The purpose of the present invention is to provide a substation equipment operation and maintenance diagnosis system, which can collect the operation data of the equipment in real time, use advanced algorithm models to perform fault diagnosis, and realize automatic monitoring and efficient operation and maintenance of the equipment.

[0004] The embodiment of the present invention is achieved as follows: In a first aspect, the present invention provides a substation equipment operation and maintenance diagnosis system, comprising: processor; A data acquisition module in communication with the processor, for collecting operation data of substation equipment in real time; A fault diagnosis module connected to the processor in communication performs fault diagnosis on the device through a preset algorithm model according to the operation data collected by the data collection module; An early warning prompt module connected to the processor for automatically sending an early warning prompt when a fault or potential risk is diagnosed in the equipment; And an operation and maintenance management module connected to the processor for recording the operation and maintenance information of the equipment and providing equipment maintenance plans and suggestions.

[0005] In an optional implementation, the data acquisition module is used to implement multi-parameter, multi-modal data acquisition of substation equipment, and the multi-parameters include current, voltage, temperature and vibration data.

[0006] Based on the above technical solution, the data acquisition module can realize multi-parameter and multi-modal data collection of substation equipment, comprehensively reflect the operating status of the equipment, and provide rich data resources for fault diagnosis.

[0007] In an optional implementation, the data acquisition module also has data cleaning and preprocessing functions for automatically identifying and filtering abnormal data to improve the accuracy and reliability of fault diagnosis.

[0008] Based on the above technical solution, abnormal data is automatically identified and filtered to improve data quality, thereby improving the accuracy and reliability of fault diagnosis.

[0009] In an optional implementation, the fault diagnosis module uses a deep learning algorithm to process and analyze operating data to achieve automatic identification and location of faults.

[0010] Based on the above solution, the fault diagnosis module processes and analyzes the operating data through a deep learning algorithm to realize automatic identification and location of faults, thereby improving the accuracy and efficiency of fault diagnosis.

[0011] In an optional implementation, the early warning prompt module can send different levels of early warning information according to different levels of failure risks, and the pre-tensioning information can be sent in the form of text messages, emails, or system pop-up windows.

[0012] Based on the above scheme, the design method of the pre-tightening reminder module can send different levels of warning information according to different levels of failure risks, ensuring that the operation and maintenance personnel can take corresponding response measures according to the warning level.

[0013] In an optional implementation, the operation and maintenance management module is used to generate equipment operation reports and fault analysis reports to provide decision support for operation and maintenance personnel.

[0014] Based on the above solution, by generating equipment operation reports and fault analysis reports, decision support is provided to operation and maintenance personnel, helping them to formulate more scientific and reasonable operation and maintenance plans.

[0015] In an optional embodiment, the substation equipment operation and maintenance diagnosis system also includes a data storage module, which is used to store collected operation data, fault diagnosis results, early warning information and operation and maintenance management information, and supports data backup and recovery functions.

[0016] Based on the above solution, the collected operation data, fault diagnosis results, early warning information and operation and maintenance management information are securely stored, and support data backup and recovery functions to ensure data integrity and security.

[0017] In an optional implementation, the fault diagnosis module is used to continuously optimize the algorithm model based on historical fault data and operation and maintenance experience to improve the accuracy and efficiency of fault diagnosis.

[0018] Based on the above solution, the accuracy and efficiency of fault diagnosis are improved by continuously learning and optimizing the algorithm model, making the system more intelligent and efficient.

[0019] In an optional implementation, the early warning prompt module is used to support customized early warning strategies and threshold settings, and users can flexibly adjust early warning conditions and levels according to actual needs.

[0020] Based on the above solution, users are allowed to customize warning conditions and levels according to actual needs, making the warning more flexible and accurate and meeting the personalized needs of different users.

[0021] In an optional implementation, the operation and maintenance management module can support integration with other enterprise information systems, realize data sharing and intercommunication, and improve the efficiency and convenience of operation and maintenance management.

[0022] Based on the above solution, data sharing and interoperability with other enterprise information systems can be achieved, the efficiency and convenience of operation and maintenance management can be improved, and the digital transformation and intelligent upgrading of enterprises can be promoted.

[0023] The beneficial effects of the embodiments of the present invention include, for example: 1. It can collect the operation data of the equipment in real time and provide accurate and comprehensive data support for fault diagnosis.

[0024] 2. Fault diagnosis is performed through advanced algorithm models, which improves the accuracy and efficiency of diagnosis.

[0025] 3. Automatically send early warning information to help operation and maintenance personnel promptly discover and handle equipment failures, reducing operation and maintenance costs.

[0026] 4. Provide comprehensive operation and maintenance management functions, including the generation of equipment operation reports and fault analysis reports, to provide support for operation and maintenance decisions.

[0027] In summary, the substation equipment operation and maintenance diagnosis system of the present invention has significant technical advantages and practical value, can greatly improve the operation and maintenance efficiency and reliability of substation equipment, and provide strong support for the development of the power industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 This is a control flow chart of a substation equipment operation and maintenance diagnosis system according to an embodiment of the present invention.

[0030] icon: 100 - processor; 200 - data acquisition module; 300 - fault diagnosis module; 400 - pre-tightening reminder module; 500 - operation and maintenance management module; 600 - data storage module. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0032] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0034] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the product of the invention is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0035] In addition, the terms "horizontal", "vertical" and the like do not mean that the components are required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0036] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. Example

[0037] Please combine Figure 1 This embodiment provides a substation equipment operation and maintenance diagnosis system, which includes: Processor 100; The data acquisition module 200 is connected to the processor 100 in communication, and is used to collect the operation data of the substation equipment in real time; The fault diagnosis module 300, which is connected to the processor 100 in communication, performs fault diagnosis on the device through a preset algorithm model according to the operation data collected by the data collection module 200; An early warning prompt module in communication with the processor 100 automatically sends an early warning prompt when a fault or potential risk is diagnosed in the equipment; And the operation and maintenance management module 500 is connected to the processor 100 for recording the operation and maintenance information of the equipment and providing equipment maintenance plans and suggestions.

[0038] That is to say, the substation equipment operation and maintenance diagnosis system provided in this embodiment includes a data acquisition module 200 , a fault diagnosis module 300 , an early warning prompt module and an operation and maintenance management module 500 .

[0039] The data acquisition module 200 is used to collect the operation data of the substation equipment in real time, including multi-parameter information such as current, voltage, temperature, vibration, etc. The module has a strong data processing capability and can automatically clean and pre-process data to ensure the accuracy and reliability of the data.

[0040] The fault diagnosis module 300 processes and analyzes the collected operation data based on the deep learning algorithm to realize the automatic identification and location of equipment faults. The accuracy and efficiency of fault diagnosis are improved by continuously optimizing the algorithm model.

[0041] The early warning prompt module automatically sends early warning prompt information according to the diagnosis result of the fault diagnosis module 300. The early warning information can be sent in different ways and contents according to the different fault levels, such as SMS, email or system pop-up window, so that the operation and maintenance personnel can take timely measures.

[0042] The operation and maintenance management module 500 is responsible for recording the operation and maintenance information of the equipment, including fault history, maintenance records, etc. This module can generate equipment operation reports and fault analysis reports to provide decision support for operation and maintenance personnel. At the same time, the operation and maintenance management module 500 also supports integration with other enterprise information systems to achieve data sharing and interoperability.

[0043] It should be understood that when implementing this embodiment, the operation data of the substation equipment is first collected in real time through the data acquisition module 200, and the data is transmitted to the fault diagnosis module 300. The fault diagnosis module 300 uses a preset algorithm model to process and analyze the data to identify whether the equipment has a fault or potential risk. Once a fault is diagnosed, the early warning prompt module will automatically send the corresponding early warning information to the operation and maintenance personnel. The operation and maintenance personnel take corresponding measures according to the early warning information, and can also view the operation and maintenance information of the equipment in the operation and maintenance management module 500 to formulate a more scientific and reasonable operation and maintenance plan.

[0044] In addition, the present invention also includes a data storage module 600, which is used to safely store the collected operation data, fault diagnosis results, early warning information, and operation and maintenance management information, and supports data backup and recovery functions. This helps to ensure the integrity and security of the data and provides strong support for subsequent operation and maintenance management.

[0045] In this embodiment, optionally, the data acquisition module 200 is used to realize multi-parameter and multi-modal data acquisition of substation equipment, and the multi-parameters include current, voltage, temperature and vibration data.

[0046] It should be understood that the data acquisition module 200 can realize multi-parameter and multi-modal data acquisition of substation equipment, comprehensively reflect the operating status of the equipment, and provide rich data resources for fault diagnosis.

[0047] Furthermore, multi-parameter data collection is as follows: The data acquisition module 200 is designed with a dedicated sensor interface, which can connect a variety of sensors to realize the collection of current, voltage, temperature and vibration data; for the collection of current and voltage data, the module adopts a high-precision current-voltage converter to ensure the accuracy and stability of the data; the collection of temperature data is realized through a temperature sensor, which can monitor the temperature changes of the equipment in real time; the collection of vibration data is carried out through a vibration sensor, which can capture the vibration information of the equipment during operation, providing a basis for fault warning and diagnosis.

[0048] Multimodal data collection is as follows: The data acquisition module 200 has multiple data acquisition modes, including real-time acquisition, periodic acquisition and event-triggered acquisition; the real-time acquisition mode can continuously acquire equipment data to provide data support for real-time monitoring and early warning; the periodic acquisition mode performs data acquisition at set time intervals, which is suitable for scenarios where equipment performance is regularly evaluated; the event-triggered acquisition mode automatically starts data acquisition when a specific event (such as a fault, anomaly, etc.) occurs in the equipment, so as to obtain data information when the fault occurs in a timely manner.

[0049] Data processing and transmission are as follows: The data acquisition module 200 has a built-in data processing unit, which can perform preliminary processing on the collected raw data, such as filtering and denoising, to improve data quality; the module has a data transmission function, which can transmit the processed data to a data center or monitoring platform via wired or wireless means to realize remote access and analysis of data.

[0050] In this embodiment, optionally, the data acquisition module 200 also has data cleaning and preprocessing functions for automatically identifying and filtering abnormal data to improve the accuracy and reliability of fault diagnosis.

[0051] It should be understood that by automatically identifying and filtering abnormal data, data quality is improved, thereby improving the accuracy and reliability of fault diagnosis.

[0052] Furthermore, the data cleaning function is as follows: The data acquisition module 200 has a built-in data cleaning algorithm that can automatically identify and process abnormal data; for abnormal data that exceeds a reasonable range or is obviously erroneous, the module can automatically eliminate or correct it to ensure the accuracy and validity of the data; the module can also deduplicate duplicate data according to preset rules or algorithms to avoid the impact of data redundancy on subsequent analysis.

[0053] The data preprocessing functions are as follows: The data acquisition module 200 has data preprocessing capabilities and can perform preliminary processing and organization on the collected raw data; the module can standardize the data and convert data of different dimensions and units into a unified standard form to facilitate subsequent data analysis and comparison; in addition, the module can also perform smoothing, denoising and other operations on the data as needed to improve the quality and stability of the data.

[0054] The collaboration with fault diagnosis is as follows: The data cleaning and preprocessing functions of the data acquisition module 200 are intended to improve the accuracy and reliability of fault diagnosis; the cleaned and preprocessed data can more accurately reflect the operating status and performance changes of the equipment, providing more powerful data support for fault diagnosis; the module can be seamlessly connected with the fault diagnosis system to achieve real-time transmission and sharing of data, thereby improving the efficiency and accuracy of fault diagnosis.

[0055] In this embodiment, optionally, the fault diagnosis module 300 uses a deep learning algorithm to process and analyze the operating data to achieve automatic identification and location of faults.

[0056] It should be understood that the fault diagnosis module 300 processes and analyzes the operating data through a deep learning algorithm to achieve automatic identification and location of faults, thereby improving the accuracy and efficiency of fault diagnosis.

[0057] Further, the application of deep learning algorithms is as follows: The fault diagnosis module 300 uses advanced deep learning algorithms, such as convolutional neural networks (CNN), recurrent neural networks (RNN) or their variants, to process and analyze the operating data of substation equipment; by building a deep learning model, the module can automatically learn the characteristics and rules in the data to achieve accurate identification and judgment of the equipment status.

[0058] Automatic fault identification is as follows: By learning from a large amount of historical data, the deep learning model can identify the differences between the normal operating mode and failure mode of the equipment; when the newly collected operating data is similar to the failure mode, the model can automatically trigger the fault identification mechanism and give corresponding fault prompts or alarm information.

[0059] The fault location functions are as follows: The fault diagnosis module 300 can not only identify the occurrence of a fault, but also preliminarily locate the fault based on the characteristics of the operating data; by analyzing the correlation between different parameters and modal data, the module can determine the part or component where the fault may occur, and provide maintenance personnel with targeted troubleshooting and repair suggestions.

[0060] The continuous optimization of the model is as follows: The fault diagnosis module 300 has the ability to optimize the model and can iterate and update the deep learning model by continuously receiving new operating data and feedback information; with the accumulation of data and the improvement of the model, the fault diagnosis accuracy and positioning accuracy of the module will continue to improve.

[0061] In this embodiment, the early warning prompt module can optionally send different levels of early warning information according to different levels of failure risks, and the early warning information can be sent in the form of text messages, emails or system pop-up windows.

[0062] It should be understood that the design of the pre-tensioning prompt module 400 can send different levels of warning information according to different levels of failure risks, ensuring that the operation and maintenance personnel can take corresponding countermeasures according to the warning level.

[0063] Furthermore, the fault risk levels are classified as follows: The early warning module can classify the fault risks into different levels, such as minor, general, severe, etc., according to the diagnosis results of the fault diagnosis module 300; each level corresponds to a different degree of fault impact and emergency processing requirements, so as to send early warning information in a targeted manner.

[0064] The multi-form warning information is sent as follows: The early warning prompt module supports multiple ways of sending warning information, including SMS, email and system pop-up windows; the module can select the most appropriate sending method based on the recipient's preferences or preset rules to ensure that the warning information can be conveyed to relevant personnel in a timely and effective manner.

[0065] The warning content is customized as follows: For different levels of failure risks, the early warning prompt module can send different levels of early warning information; The warning information includes the fault type, level, impact scope, recommended measures, etc., so that the recipient can quickly understand the fault situation and take appropriate countermeasures.

[0066] The early warning information management and records are as follows: The early warning prompt module has the functions of managing and recording early warning information, and can save all sent early warning information and its sending records; Managers can view historical warning information through the system interface and evaluate and improve the warning effects.

[0067] In this embodiment, the operation and maintenance management module 500 is optionally used to generate an operation report and a fault analysis report of the equipment to provide decision support for the operation and maintenance personnel.

[0068] It should be understood that by generating equipment operation reports and fault analysis reports, decision support is provided to operation and maintenance personnel, helping them to formulate more scientific and reasonable operation and maintenance plans.

[0069] Furthermore, the equipment operation report is generated as follows: The operation and maintenance management module 500 can generate equipment operation reports based on the real-time and historical data provided by the data acquisition module 200; The report content includes the equipment's operating status, key parameter change trends, performance evaluation, etc., which are presented in the form of charts and text, so that operation and maintenance personnel can intuitively understand the overall operation of the equipment; The module supports customized report generation, allowing users to select report content and format based on their needs.

[0070] The fault analysis report is generated as follows: The operation and maintenance management module 500 can generate a fault analysis report by combining the diagnosis result of the fault diagnosis module 300 and the warning information of the warning prompt module; The report records in detail the time, location, type, impact range, etc. of the fault, and analyzes the cause of the fault and possible solutions; The module can also provide analysis of fault patterns and trends based on historical fault data, helping operation and maintenance personnel predict and prevent potential faults in advance.

[0071] The decision support functions are as follows: The operation and maintenance management module 500 provides decision support for operation and maintenance personnel through equipment operation reports and fault analysis reports; Based on the data and analysis results in the report, operation and maintenance personnel can formulate targeted operation and maintenance strategies, optimize equipment configuration and maintenance plans, and improve operation and maintenance efficiency and equipment reliability; The module also supports data visualization and interactive analysis, making it easier for operation and maintenance personnel to conduct in-depth data exploration and decision analysis.

[0072] Report management and sharing: The operation and maintenance management module 500 has report management and sharing functions, and can save and manage the generated operation reports and fault analysis reports; Operation and maintenance personnel can view and export reports through the system interface, and can also share reports with other relevant personnel or departments to promote information sharing and collaboration.

[0073] In this embodiment, optionally, the substation equipment operation and maintenance diagnosis system also includes a data storage module 600 that is communicatively connected to the processor 100. The data storage module 600 is used to store collected operation data, fault diagnosis results, early warning information, and operation and maintenance management information, and supports data backup and recovery functions.

[0074] It should be understood that the collected operating data, fault diagnosis results, early warning information and operation and maintenance management information will be securely stored, and support data backup and recovery functions to ensure data integrity and security.

[0075] In this embodiment, optionally, the fault diagnosis module 300 is used to continuously optimize the algorithm model according to historical fault data and operation and maintenance experience to improve the accuracy and efficiency of fault diagnosis.

[0076] It should be understood that by continuously learning and optimizing the algorithm model, the accuracy and efficiency of fault diagnosis can be improved, making the system more intelligent and efficient.

[0077] In this embodiment, the early warning prompt module is optionally used to support customized early warning strategies and threshold settings, and the user can flexibly adjust the early warning conditions and levels according to actual needs.

[0078] It should be understood that allowing users to customize warning conditions and levels according to actual needs makes warnings more flexible and accurate and meets the personalized needs of different users.

[0079] In this embodiment, the operation and maintenance management module 500 can optionally support integration with other enterprise information systems to achieve data sharing and intercommunication, thereby improving the efficiency and convenience of operation and maintenance management.

[0080] It should be understood that data sharing and interoperability with other enterprise information systems can be achieved, the efficiency and convenience of operation and maintenance management can be improved, and the digital transformation and intelligent upgrading of enterprises can be promoted.

[0081] It should be noted that the implementation of each module of the substation equipment operation and maintenance diagnosis system provided in this embodiment is as follows: First, the implementation of the data acquisition module 200 The data acquisition module 200 is responsible for real-time acquisition of substation equipment operating data. First, the module acquires the unstructured data and structured data of the equipment by exchanging data with non-powered detection equipment and powered detection equipment. The unstructured data mainly includes real-time monitoring information such as the temperature and vibration of the equipment, while the structured data includes parameters such as the voltage and current of the equipment. At the same time, the module also has data cleaning and preprocessing functions, which can automatically identify and filter abnormal data to ensure the accuracy and reliability of the data.

[0082] Second, the implementation of the fault diagnosis module 300 The fault diagnosis module 300 processes and analyzes the collected operating data based on the deep learning algorithm. First, the module uses signal processing technology to process and analyze signals such as voltage and current to determine the type and location of the fault. For example, the characteristics of the fault signal are extracted by wavelet transform, power spectrum analysis and other methods. Secondly, artificial intelligence algorithms such as neural networks and genetic algorithms are used to establish a fault diagnosis model, analyze and learn a large amount of data, and achieve accurate judgment and prediction of faults. In addition, when the capacity of the online monitoring and fault diagnosis system is limited, the expert system diagnosis method can also be used for comprehensive analysis and processing, combining system analysis with expert judgment methods to clarify the necessity of equipment maintenance and operation, and formulate a scientific and reasonable operation and maintenance plan.

[0083] Third, the implementation of the early warning module The early warning prompt module automatically sends early warning prompt information according to the diagnosis results of the fault diagnosis module 300. The sending method of the early warning information can be configured according to actual needs, including but not limited to SMS, email, system pop-up window and other forms. In order to ensure the timeliness and accuracy of the early warning information, the power department can also appropriately promote mobile application technology, use the mobile terminal early warning message push function, and push the early warning information of the online monitoring data of the primary equipment to the power operation and maintenance personnel in real time, provide information reference for the operation and maintenance personnel, so that they can fully carry out inspection and maintenance work in accordance with the early warning push message.

[0084] Fourth, the implementation of the operation and maintenance management module 500 The operation and maintenance management module 500 is responsible for recording the operation and maintenance information of the equipment, including fault history, maintenance records, etc. This module can generate equipment operation reports and fault analysis reports to provide decision support for operation and maintenance personnel. At the same time, the operation and maintenance management module 500 also supports integration with other enterprise information systems to achieve data sharing and intercommunication, and improve the efficiency and convenience of operation and maintenance management. In addition, in order to ensure the smooth progress of operation and maintenance work, a maintenance system can also be established to clarify equipment maintenance plans, maintenance forms, maintenance records, etc., so that each operation and maintenance personnel is clear about their job responsibilities and operates in accordance with regulations.

[0085] The beneficial effects of the embodiments of the present invention include, for example: 1. It can collect the operation data of the equipment in real time and provide accurate and comprehensive data support for fault diagnosis.

[0086] 2. Fault diagnosis is performed through advanced algorithm models, which improves the accuracy and efficiency of diagnosis.

[0087] 3. Automatically send early warning information to help operation and maintenance personnel promptly discover and handle equipment failures, reducing operation and maintenance costs.

[0088] 4. Provide comprehensive operation and maintenance management functions, including the generation of equipment operation reports and fault analysis reports, to provide support for operation and maintenance decisions.

[0089] In summary, the substation equipment operation and maintenance diagnosis system of the present invention realizes automatic monitoring and efficient operation and maintenance of equipment by collecting the operation data of the equipment in real time and using advanced algorithm models for fault diagnosis. At the same time, through the implementation of the early warning prompt module and the operation and maintenance management module 500, the reaction speed and handling ability of the operation and maintenance personnel to equipment failures are improved, the operation and maintenance costs are reduced, and the service life of the equipment is extended. In addition, through the application of the mobile terminal early warning message push function, the timeliness and accuracy of the early warning information are further improved, providing a more convenient and efficient working method for power operation and maintenance personnel.

[0090] At the same time, the substation equipment operation and maintenance diagnosis system of the present invention has significant technical advantages and practical value, can greatly improve the operation and maintenance efficiency and reliability of substation equipment, and provide strong support for the development of the power industry.

[0091] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A substation equipment operation and maintenance diagnosis system, characterized in that: include: Processor(100); A data acquisition module (200) in communication with the processor (100), used for collecting operation data of substation equipment in real time; A fault diagnosis module (300) connected to the processor (100) for performing fault diagnosis on the device using a preset algorithm model based on the operating data collected by the data collection module (200); An early warning prompt module connected in communication with the processor (100) automatically sends an early warning prompt when a fault or potential risk is diagnosed in the equipment; And an operation and maintenance management module (500) which is communicatively connected to the processor (100) and is used to record operation and maintenance information of the equipment and provide equipment maintenance plans and suggestions.

2. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The data acquisition module (200) is used to realize multi-parameter and multi-modal data acquisition of substation equipment, wherein the multi-parameters include current, voltage, temperature and vibration data.

3. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The data acquisition module (200) also has data cleaning and preprocessing functions, and is used to automatically identify and filter abnormal data, thereby improving the accuracy and reliability of fault diagnosis.

4. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The fault diagnosis module (300) uses a deep learning algorithm to process and analyze operating data, thereby achieving automatic identification and location of faults.

5. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The early warning prompt module can send different levels of early warning information according to different levels of failure risks. The early warning information can be sent in the form of text messages, emails or system pop-up windows.

6. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The operation and maintenance management module (500) is used to generate equipment operation reports and fault analysis reports, and provide decision support for operation and maintenance personnel.

7. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The substation equipment operation and maintenance diagnosis system further comprises a data storage module (600), wherein the data storage module (600) is used to store collected operation data, fault diagnosis results, early warning information and operation and maintenance management information, and supports data backup and recovery functions.

8. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The fault diagnosis module (300) is used to continuously optimize the algorithm model based on historical fault data and operation and maintenance experience, thereby improving the accuracy and efficiency of fault diagnosis.

9. The substation equipment operation and maintenance diagnostic system according to claim 1, characterized in that: The warning prompt module is used to support customized warning strategies and threshold settings, and users can flexibly adjust warning conditions and levels according to actual needs.

10. The substation equipment operation and maintenance diagnosis system according to claim 1, characterized in that: The operation and maintenance management module (500) can support integration with other enterprise information systems, realize data sharing and intercommunication, and improve the efficiency and convenience of operation and maintenance management.

Images