Secondary circuit fault diagnosis positioning method and system

Abstract

The invention discloses a secondary circuit fault diagnosis and positioning method and system, and the method comprises the steps: obtaining the topological structure and equipment information of a secondary circuit according to a configuration file of the secondary circuit of a transformer substation, and constructing a fault map containing all equipment nodes of the secondary circuit and the connection relation of the equipment nodes; operating data of the secondary circuit are collected in real time, and faults are recognized; reasoning a fault link path based on the fault map, and determining an abnormal fault source and a corresponding link path; and the fault link path is displayed on a visual interface of the fault map, and the specific position of the fault equipment is identified. By fusing the intelligent substation secondary circuit configuration file, the real-time operation data and the graph visualization technology, automatic identification, link path reasoning and accurate positioning of abnormal faults are achieved, the timeliness and accuracy of fault identification are improved, fault links are visually highlighted on a graphical interface, the positions of fault equipment are clearly identified, and the fault identification efficiency is improved. The operation and maintenance efficiency is greatly improved, and the troubleshooting difficulty is reduced.

Description

Technical Field

[0001] This invention relates to the field of smart grids, and specifically to a method and system for diagnosing and locating secondary circuit faults. Background Technology

[0002] With the rapid development of smart grids and digital substations, the secondary circuits of substations, as key infrastructure supporting equipment monitoring, control, protection, and communication, are becoming increasingly complex. Traditional substations mainly rely on physical cable connections and paper circuit diagrams, and maintenance work heavily depends on manual inspections and experience-based fault diagnosis. Faced with increasingly complex circuit topologies and massive signal interactions, traditional methods often struggle to quickly and accurately locate fault points, leading to longer fault handling cycles and increased operational risks.

[0003] In recent years, with the widespread adoption of virtual loops and digital network communication technologies in smart substations, secondary systems have achieved a high degree of integration in data acquisition, signal transmission, and equipment interconnection, further increasing the difficulty of system operation and maintenance and fault diagnosis. Currently, some secondary loop visualization technologies have attempted to generate topology diagrams by parsing configuration files to intuitively display the overall system structure, but they still have significant shortcomings in complex fault link analysis, real-time identification of abnormal states, and root cause localization.

[0004] Against this backdrop, artificial intelligence methods have been gradually introduced into the field of power system fault diagnosis, leveraging data mining and pattern recognition technologies to improve the accuracy and efficiency of anomaly detection. However, existing technical solutions mostly focus on fault type identification and lack the ability to perform full-path reasoning and visual diagnosis of circuit links. Furthermore, in the fault location phase, traditional methods struggle to effectively correlate virtual diagnostic results with physical equipment, still requiring manual comparison of numbers or tag searches, which hinders the improvement of overall operation and maintenance efficiency.

[0005] Therefore, in the context of increasingly complex and digitalized secondary circuits, how to build an efficient operation and maintenance system with full-path analysis, real-time diagnosis and virtual-physical linkage capabilities has become a key issue that urgently needs to be addressed in the intelligent operation and maintenance of power systems. Summary of the Invention

[0006] The technical problem to be solved by this invention is to provide a secondary circuit fault diagnosis and location method and system that can quickly identify and accurately locate abnormal faults in the secondary circuit, improve fault handling efficiency, reduce operation and maintenance difficulty, and enhance the intuitiveness and accuracy of fault diagnosis by highlighting the fault link path through a visual interface.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention includes the following steps: S1. Obtain the topology and equipment information of the secondary circuit based on the configuration description file of the secondary circuit of the intelligent substation, and construct an abnormal fault map containing each equipment node of the secondary circuit and its connection relationship. S2 collects and monitors the operating data of the secondary circuit in real time and identifies abnormal faults; S3, based on the fault map, reason about the link path of the detected abnormal fault to determine the source of the abnormal fault and the corresponding link path. S4. Highlight the fault link path on the visualization interface of the abnormal fault map and identify the specific location of the faulty device.

[0008] Furthermore, step S2 includes: S21, acquire secondary circuit operation data from any one or more of the data sources of the protection device, the measurement and control device and the sensor; S22, perform fusion processing on the operating data of the secondary circuit and extract abnormal features; S23 uses deep learning algorithms to analyze the fused data and identify characteristic signals of abnormal faults.

[0009] Furthermore, the deep learning algorithm described in step S23 is based on a graph neural network model.

[0010] Furthermore, step S3 includes: S31, the corresponding node where the abnormal fault was detected is marked as the starting point in the fault map; S32, using a graph search algorithm, traverse the fault graph along the connection relationship of the starting node to infer at least one fault link path; S33, determine the fault source node based on the fault link path, and generate the corresponding fault link path.

[0011] Furthermore, step S4 includes: S41, The secondary circuit fault map is visualized on the graphical interface; S42, the fault link path and fault point obtained by reasoning are highlighted on the interface; S43 provides interactive functionality to allow users to view detailed information about the fault point through the interface.

[0012] Furthermore, it also includes: S5, use an RFID reader / writer to read and identify the RFID tag information configured on the faulty part; send a control command to the RFID tag to light up its LED indicator, thereby visually indicating the location of the faulty part at the fault site.

[0013] Furthermore, it also includes: S6 matches the detected abnormal features and the inferred fault paths with the pre-established fault knowledge base; the preset expert system provides fault cause analysis and handling suggestions based on the matching results to assist in completing fault diagnosis.

[0014] The present invention also provides a secondary circuit fault diagnosis and location system, comprising a processor and a computer-readable storage medium interconnected thereto, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by the processor to implement the steps of the above-described secondary circuit fault diagnosis and location method.

[0015] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described secondary circuit fault diagnosis and location method.

[0016] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-described secondary circuit fault diagnosis and location method.

[0017] Compared with the prior art, the advantages of the present invention are as follows: This invention proposes a method to obtain the topology and equipment information of the secondary circuits in a smart substation based on the configuration description file, and construct an abnormal fault map containing the nodes of each device in the secondary circuit and their connection relationships. It then collects and monitors the operating data of the secondary circuits in real time to identify abnormal faults; based on the fault map, it infers the link paths of the detected abnormal faults to determine the source of the abnormal fault and the corresponding fault link path; and highlights the fault link path on the visualization interface of the abnormal fault map, marking the specific location of the faulty equipment. This technical solution integrates the configuration file of the secondary circuits in the smart substation, real-time operating data, and map visualization technology to achieve automatic identification, link path inference, and precise location of abnormal faults. This improves the timeliness and accuracy of fault identification, intuitively highlights fault links on the graphical interface, and clearly marks the location of faulty equipment, significantly improving operation and maintenance efficiency and reducing the difficulty of fault diagnosis. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the process of this embodiment. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and specific preferred embodiments, but this does not limit the scope of protection of the present invention.

[0020] The technical solution adopted in this embodiment is as follows: Figure 1 As shown, it includes the following steps: S1. Obtain the topology and equipment information of the secondary circuit based on the configuration description file of the secondary circuit of the intelligent substation, and construct an abnormal fault map containing each equipment node of the secondary circuit and its connection relationship. S2 collects and monitors the operating data of the secondary circuit in real time and identifies abnormal faults; S3, based on the fault map, reason about the link path of the detected abnormal fault to determine the source of the abnormal fault and the corresponding link path. S4. Highlight the fault link path on the visualization interface of the abnormal fault map and identify the specific location of the faulty device.

[0021] This embodiment proposes to obtain the topology and equipment information of the secondary circuits of a smart substation based on the configuration description file of the secondary circuits, and construct an abnormal fault map containing the various equipment nodes of the secondary circuits and their connection relationships; collect and monitor the operating data of the secondary circuits in real time to identify abnormal faults; infer the link paths of the detected abnormal faults based on the fault map to determine the source of the abnormal fault and the corresponding fault link path; highlight the fault link path on the visualization interface of the abnormal fault map, and mark the specific location of the faulty equipment. The technical solution of this embodiment achieves automatic identification, link path reasoning, and precise location of abnormal faults by integrating the configuration file of the secondary circuits of the smart substation, real-time operating data, and map visualization technology. This improves the timeliness and accuracy of fault identification, intuitively highlights the fault link on the graphical interface, and clearly marks the location of the faulty equipment, significantly improving operation and maintenance efficiency and reducing the difficulty of fault diagnosis.

[0022] Preferably, step S2 includes: S21, acquire secondary circuit operation data from any one or more of the data sources of the protection device, the measurement and control device and the sensor; S22, perform fusion processing on the operating data of the secondary circuit and extract abnormal features; S23 uses deep learning algorithms to analyze the fused data and identify characteristic signals of abnormal faults.

[0023] Preferably, the deep learning algorithm described in step S23 is based on a graph neural network model.

[0024] Preferably, step S3 includes: S31, the corresponding node where the abnormal fault was detected is marked as the starting point in the fault map; S32, using a graph search algorithm, traverse the fault graph along the connection relationship of the starting node to infer at least one fault link path; S33, determine the fault source node based on the fault link path, and generate the corresponding fault link path.

[0025] Preferably, step S4 includes: S41, The secondary circuit fault map is visualized on the graphical interface; S42, the fault link path and fault point obtained by reasoning are highlighted on the interface; S43 provides interactive functionality to allow users to view detailed information about the fault point through the interface.

[0026] Preferred options also include: S5, use an RFID reader / writer to read and identify the RFID tag information configured on the faulty part; send a control command to the RFID tag to light up its LED indicator, thereby visually indicating the location of the faulty part at the fault site.

[0027] Preferred options also include: S6 matches the detected abnormal features and the inferred fault paths with the pre-established fault knowledge base; the preset expert system provides fault cause analysis and handling suggestions based on the matching results to assist in completing fault diagnosis.

[0028] This embodiment also provides a secondary circuit fault diagnosis and location system, including a processor and a computer-readable storage medium connected to each other. The computer-readable storage medium stores a computer program, which is executed by the processor to implement the steps of the above-described secondary circuit fault diagnosis and location method.

[0029] This embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described secondary circuit fault diagnosis and location method.

[0030] This embodiment also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-described secondary circuit fault diagnosis and location method.

[0031] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0032] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for diagnosing and locating faults in a secondary circuit, characterized in that, include: S1. Obtain the topology and equipment information of the secondary circuit based on the configuration description file of the secondary circuit of the smart substation, and construct an abnormal fault map containing each equipment node of the secondary circuit and its connection relationship. S2 collects and monitors the operating data of the secondary circuit in real time and identifies abnormal faults; S3, based on the fault map, reason about the link path of the detected abnormal fault to determine the source of the abnormal fault and the corresponding link path. S4. Highlight the fault link path on the visualization interface of the abnormal fault map and identify the specific location of the faulty device.

2. The method for diagnosing and locating secondary circuit faults according to claim 1, characterized in that, Step S2 includes: S21, acquire secondary circuit operation data from any one or more of the data sources of the protection device, the measurement and control device and the sensor; S22, perform fusion processing on the operation data of the multiple loops and extract abnormal features; S23 uses deep learning algorithms to analyze the fused data and identify characteristic signals of abnormal faults.

3. The method for diagnosing and locating secondary circuit faults according to claim 2, characterized in that, The deep learning algorithm described in step S23 is based on a graph neural network model.

4. The method for diagnosing and locating secondary circuit faults according to claim 1, characterized in that, Step S3 includes: S31, the corresponding node where the abnormal fault was detected is marked as the starting point in the fault map; S32, using a graph search algorithm, traverse the fault graph along the connection relationship of the starting node to infer at least one fault link path; S33, determine the fault source node based on the fault link path, and generate the corresponding fault link path.

5. The method for diagnosing and locating secondary circuit faults according to claim 1, characterized in that, Step S4 includes: S41, The secondary circuit fault map is visualized on the graphical interface; S42, the fault link path and fault point obtained by reasoning are highlighted on the interface; S43 provides interactive functionality to allow users to view detailed information about the fault point through the interface.

6. The method for diagnosing and locating secondary circuit faults according to claim 1, characterized in that, Also includes: S5, use RFID reader / writer to read and identify the RFID tag information configured on the faulty part; Send control commands to the RFID tag to light up its LED indicator, thereby visually indicating the location of the fault at the fault site.

7. The method for diagnosing and locating secondary circuit faults according to claim 1, characterized in that, Also includes: S6, Match and compare the detected abnormal features and the inferred fault paths with the pre-established fault knowledge base; The pre-set expert system provides fault cause analysis and handling suggestions based on the matching results to assist in fault diagnosis.

8. A secondary circuit fault diagnosis and location system, characterized in that, The method includes an interconnected processor and a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and the computer program is executed by the processor to implement the steps of the secondary circuit fault diagnosis and location method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the secondary circuit fault diagnosis and location method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes a computer program, which, when executed by a processor, implements the steps of the secondary circuit fault diagnosis and location method according to any one of claims 1 to 7.

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