A model-based power regulation system fault analysis method, device and system
By establishing a fault cause model library and a graphical configuration interface, the automation and standardization of fault analysis in power control systems have been achieved, solving the problem of high technical barriers for operation and maintenance personnel and improving the efficiency and accuracy of fault location.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NARI NANJING CONTROL SYSTEM CO LTD
- Filing Date
- 2026-02-02
- Publication Date
- 2026-06-19
Smart Images
Figure CN122243447A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of intelligent operation and maintenance technology, and relates to a model-based method, device and system for fault analysis in power control systems. Background Technology
[0002] The stable operation of a power control system depends on the reliability and real-time performance of its data acquisition subsystem. When a fault occurs in the data acquisition subsystem, such as data interruption, jumps, or anomalies, traditional troubleshooting methods heavily rely on maintenance personnel's in-depth understanding of the underlying hardware and software, network protocols, and software code details. This reliance leads to inefficient fault location, long response times, and extremely high skill requirements for maintenance personnel, making it difficult to effectively transfer and solidify knowledge.
[0003] While related technologies exist, including alarm and simple log query tools based on fixed rules, their analysis processes are often fragmented and unstructured, lacking systematic encapsulation and reuse of expert analysis logic. Operations personnel still need to manually correlate and analyze massive amounts of system information, a tedious and error-prone process. Summary of the Invention
[0004] Objective: In view of at least one of the above technical problems, this application aims to address the high technical threshold and low analysis efficiency caused by the need for maintenance personnel to master complex software implementation details when conducting fault analysis. It provides a model-based fault analysis method, device, and system for power control systems, which transforms abstract fault analysis ideas into a standardized, executable, and user-friendly automated analysis process. This decouples the fault location process from complex technical details, thereby significantly optimizing the operation and maintenance management efficiency of the data acquisition system.
[0005] The technical solution adopted in this application is as follows:
[0006] Firstly, this application provides a model-based fault analysis method for power control systems, including:
[0007] S1, extract abnormal events that trigger faults in the power control system, and establish a corresponding fault cause model for each abnormal event to form a fault cause model library; the fault cause model encapsulates the correlation between abnormal events and information from the acquisition system, as well as verification rules for determining whether an abnormal event has occurred.
[0008] S2, Based on the fault type, at least one fault cause model is retrieved from the fault cause model library in logical order using a graphical configuration interface to generate a structured fault analysis process.
[0009] S3 automatically executes the fault analysis process, sequentially verifies the abnormal events associated with the fault cause model in the fault analysis process, outputs fault location results or analysis failure indications based on the verification results, and generates execution records.
[0010] In some embodiments, the method further includes:
[0011] S4. Generate execution data based on the execution records of historical fault analysis processes. Based on the execution data, generate recommended templates for fault analysis processes of each fault type according to preset indicators for reference in the subsequent fault analysis process generation.
[0012] In some embodiments, in step S4, the execution data includes at least one of fault location accuracy, process execution success rate, and average process time.
[0013] In some embodiments, in step S4, the preset index is at least one of the following: fault location accuracy threshold, process execution success rate threshold, and average process time threshold.
[0014] In some embodiments, in step S1, the collected system information includes one or more of system logs, operational alarms, performance indicators, and configuration information.
[0015] In some embodiments, in step S1, the abnormal event includes at least one of network interruption, buffer full, service process abnormality, data acquisition timeout, or data quality abnormality.
[0016] In some embodiments, in step S2, the graphical configuration interface is a visual logic orchestration interface, used to construct a fault analysis process with a sequential order by dragging and dropping fault cause model icons and establishing connection lines.
[0017] In some embodiments, step S3 involves verifying the abnormal events associated with the fault cause model in the fault analysis process, including:
[0018] Based on the correlation in the fault cause model, the corresponding real-time acquisition system information is automatically obtained (queried or collected);
[0019] Based on the verification rules in the fault cause model, determine whether the corresponding abnormal event has occurred according to the real-time collected system information.
[0020] If the corresponding abnormal event is determined to have occurred, the corresponding fault location result is output and the process is terminated.
[0021] If it is determined that none of the abnormal events associated with all fault cause models in the fault analysis process have occurred, an analysis failure indication will be output.
[0022] In this embodiment, by sorting out typical scenarios, historical fault cases and expert experience of power control system acquisition faults, abnormal events that trigger power control system acquisition faults are extracted; based on the acquisition business mechanism of power control system, the causal relationship between abnormal events and acquisition system information is formally defined to form a fault cause model corresponding to the abnormal events.
[0023] It should be noted that the fault cause model library supports dynamic updates, and can add, modify or delete fault cause models based on new typical fault scenarios, fault cases and expert experience.
[0024] Secondly, this application provides a model-based power control system fault analysis acquisition device, including a processor and a storage medium;
[0025] The storage medium is used to store instructions;
[0026] The processor is configured to operate according to the instructions to execute the method according to the first aspect.
[0027] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.
[0028] Fourthly, this application provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect.
[0029] Fifthly, this application provides a model-based power control system for fault acquisition and analysis, comprising:
[0030] At least one of the aforementioned fault acquisition and analysis devices;
[0031] The data acquisition subsystem of the power control system is used to provide information from the data acquisition system;
[0032] A communication network is used to establish a data interaction link between the fault analysis device and the acquisition subsystem to transmit acquisition system information and fault analysis instructions.
[0033] Beneficial effects: The model-based power control system fault analysis method, device, and system provided in this application have the following advantages:
[0034] (1) By solidifying expert experience into a standardized fault cause model and adopting an intuitive graphical configuration method, ordinary maintenance personnel can complete professional-level fault analysis without having to deeply understand the complex technical details of the underlying code and protocols, which effectively solves the problem of over-reliance on senior technical experts.
[0035] (2) The analysis process was automated, reducing the time spent on fault analysis from hours to minutes. The structured model and process ensured the standardization and repeatability of the analysis process, reduced human error, and improved the accuracy of fault location.
[0036] (3) The fault cause model library and analysis process become reusable and accumulative knowledge assets. Through historical data analysis and intelligent recommendation mechanism, the system can continuously learn and optimize, so that the fault analysis strategy can evolve with practice, improve the overall intelligence level and adaptability of the system, and realize the transformation of operation and maintenance knowledge from implicit experience to explicit digital assets.
[0037] (4) It achieves decoupling between fault analysis logic and specific software implementation. When the underlying system is upgraded or changed, only the relevant models need to be updated or adjusted, without rewriting the entire analysis logic, which greatly enhances the maintainability and adaptability of the operation and maintenance method. The visual orchestration method also enables the analysis process to respond flexibly and quickly to new fault modes. Attached Figure Description
[0038] Figure 1 This is a flowchart illustrating a model-based power control system fault analysis method according to an embodiment of this application. Detailed Implementation
[0039] The present application will be further described below with reference to the accompanying drawings and embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and should not be used to limit the scope of protection of the present application.
[0040] In the description of this application, "several" means one or more, "multiple" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.
[0041] In the description of this application, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0042] The term "and / or" simply describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0043] Example 1: This example provides a model-based fault analysis method for power control systems, such as... Figure 1 As shown, it includes:
[0044] S1. Extract abnormal events that trigger faults in the power control system and establish a corresponding fault cause model for each abnormal event to form a fault cause model library. The fault cause model encapsulates the correlation between abnormal events and information from the acquisition system, as well as verification rules for determining whether an abnormal event has occurred.
[0045] In this embodiment, by sorting out typical scenarios, historical fault cases and expert experience of power control system acquisition faults, abnormal events that trigger power control system acquisition faults are extracted; based on the acquisition business mechanism of power control system, the causal relationship between abnormal events and acquisition system information is formally defined to form a fault cause model corresponding to the abnormal events.
[0046] In some embodiments, in step S1, the collected system information includes one or more of system logs, operational alarms, performance indicators, and configuration information.
[0047] In some embodiments, in step S1, the abnormal event includes at least one of network interruption, buffer full, service process abnormality, data acquisition timeout, or data quality abnormality.
[0048] It should be noted that the fault cause model library supports dynamic updates, and can add, modify or delete fault cause models based on new typical fault scenarios, fault cases and expert experience.
[0049] S2, based on the fault type, at least one fault cause model is retrieved from the fault cause model library in logical order using a graphical configuration interface to generate a structured fault analysis process.
[0050] In some embodiments, in step S2, the graphical configuration interface is a visual logic orchestration interface, used to construct a fault analysis process with a sequential order by dragging and dropping fault cause model icons and establishing connection lines.
[0051] In this embodiment, the graphical configuration interface provides icons for preset fault cause models; based on the analysis approach, maintenance personnel can generate a structured fault analysis process by dragging and dropping model icons and establishing logical sequence connections between models.
[0052] S3 automatically executes the fault analysis process, sequentially verifies the abnormal events associated with the fault cause model in the fault analysis process, outputs fault location results or analysis failure indications based on the verification results, and generates execution records.
[0053] In some embodiments, step S3 involves verifying the abnormal events associated with the fault cause model in the fault analysis process, including:
[0054] Based on the correlation in the fault cause model, the corresponding real-time acquisition system information is automatically obtained (queried or collected);
[0055] Based on the verification rules in the fault cause model, determine whether the corresponding abnormal event has occurred according to the real-time collected system information.
[0056] If the corresponding abnormal event is determined to have occurred, the corresponding fault location result is output and the process is terminated.
[0057] If it is determined that none of the abnormal events associated with all fault cause models in the fault analysis process have occurred, an analysis failure indication will be output.
[0058] S4. Generate execution data based on the execution records of historical fault analysis processes. Based on the execution data, generate recommended templates for fault analysis processes of each fault type according to preset indicators for reference in the subsequent fault analysis process generation.
[0059] In some embodiments, in step S4, the execution data includes at least one of fault location accuracy, process execution success rate, and average process time.
[0060] In some embodiments, in step S4, the preset index is at least one of the following: fault location accuracy threshold, process execution success rate threshold, and average process time threshold.
[0061] In this step, execution records of historical fault analysis processes (including fault location results and final verification conclusions) and corresponding fault types are collected and stored. Statistical mining is performed on these execution records to obtain execution data (fault location accuracy, process execution success rate, and average process time), forming knowledge about process effectiveness and process combination patterns.
[0062] The system generates a recommended ranking of fault analysis processes for each fault type according to specified indicator requirements, and provides process combination suggestions to operations and maintenance personnel during the fault analysis process generation process in step S2. For example, it recommends a fault analysis process template with high success rate and low time consumption for a specific fault type.
[0063] Application Example: This application is implemented in a provincial power grid control system. For the operation and maintenance scenario of the data acquisition subsystem of the power grid control system, it realizes the rapid and low-threshold location and analysis of acquisition faults. The acquisition fault analysis process is as follows.
[0064] First, typical data acquisition failure cases of the provincial power grid over the past three years were reviewed, key abnormal events were extracted, and an initial failure cause model library was established based on the data acquisition business mechanism. For example:
[0065] For the "channel exit" fault type, the system invokes the network status monitoring model, port status monitoring model, and communication process status monitoring model. By analyzing the monitoring results of these three models, the "channel exit" fault type is located to a specific abnormal status category, and the corresponding root cause determination result is output. The completed model is stored in the fault cause model library in the form of a callable standardized functional model.
[0066] Next is the visualized operation and maintenance. When a dispatch center reports "Channel A exited abnormally," the user logs into the system and enters the graphical workflow orchestration interface. After selecting "Channel Exit" from the preset fault types on the interface, the system automatically associates and loads three corresponding standardized diagnostic models from the fault cause model library: "Network Status Monitoring Model," "Port Status Monitoring Model," and "Communication Process Status Monitoring Model." Based on different analytical assumptions, the operation and maintenance personnel can adjust the execution order of the three models by dragging and dropping to form an analysis workflow. For example, the logic can be adjusted as follows: first check if the network is interrupted, then check the port status, and finally check the communication process status.
[0067] Once configured, the system will automatically execute the analysis process:
[0068] 1. Network Status Analysis: Automatically query the network connection status in the log. If the network status is interrupted, it is judged as "abnormal network status" and the result is output; if it is normal, proceed to the next step.
[0069] 2. Port Status Analysis: Automatically queries the listening status of the specified TCP port (e.g., 2404). If the port is not listening or has no valid connection, it is determined as "port status abnormal" and the result is output; if normal, proceed to the next step.
[0070] 3. Communication Process Status Analysis: Automatically checks the liveness and resource usage of the acquisition process. If the process is abnormal, it is judged as "communication process failure" and the result is output; if everything is normal, the process ends and "channel not found, exit reason" is output.
[0071] The system continuously collects execution records for each analysis process. After a period of operation, data analysis revealed that for "channel exit" type faults, the process consisting of "network status" -> "port status" -> "communication process status" had the shortest average location time. Therefore, the intelligent recommendation module marked this process as the optimal template. When other operations and maintenance personnel configure similar analysis tasks again, the system will proactively recommend this template in the interface sidebar, allowing users to load and fine-tune it with a single click, greatly improving configuration and analysis efficiency.
[0072] The implementation of this embodiment verifies that the method described in this application can quickly transform abstract expert analysis ideas into standard processes that can be executed automatically. This allows ordinary maintenance personnel to reduce the average fault location time from several hours required by traditional manual troubleshooting to less than ten minutes without having to deeply understand communication protocols and software code. This truly decouples fault analysis capabilities from specific technical details and achieves the core objective of low-threshold, high-efficiency maintenance management.
[0073] Example 2: Based on Example 1, this example provides a model-based power control system fault analysis acquisition device, including a processor and a storage medium;
[0074] The storage medium is used to store instructions;
[0075] The processor is configured to operate according to the instructions to execute the method according to Embodiment 1.
[0076] Example 3: Based on Example 1, this example provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in Example 1.
[0077] Example 4: Based on Example 1, this example provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in Example 1.
[0078] Example 5: Based on Example 1, this example provides a model-based power control system for fault acquisition and analysis, including:
[0079] At least one of the aforementioned fault acquisition and analysis devices;
[0080] The data acquisition subsystem of the power control system is used to provide information from the data acquisition system;
[0081] A communication network is used to establish a data interaction link between the fault analysis device and the acquisition subsystem to transmit acquisition system information and fault analysis instructions.
[0082] 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-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0083] 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, as well as 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, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0084] These 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 function specified in one or more boxes.
[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment 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.
[0086] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.
Claims
1. A model-based fault analysis method for power control systems, characterized in that, include: S1, extract the abnormal events that trigger the faults collected by the power control system, and establish a corresponding fault cause model for each abnormal event to form a fault cause model library; The fault cause model encapsulates the correlation between abnormal events and information collected by the system, as well as verification rules for determining whether an abnormal event has occurred. S2, Based on the fault type, at least one fault cause model is retrieved from the fault cause model library in logical order using a graphical configuration interface to generate a structured fault analysis process. S3 automatically executes the fault analysis process, sequentially verifies the abnormal events associated with the fault cause model in the fault analysis process, outputs fault location results or analysis failure indications based on the verification results, and generates execution records.
2. The method according to claim 1, characterized in that, Also includes: S4. Generate execution data based on the execution records of historical fault analysis processes. Based on the execution data, generate recommended templates for fault analysis processes of each fault type according to preset indicators for reference in the subsequent fault analysis process generation.
3. The method according to claim 2, characterized in that, In step S4, the execution data includes at least one of fault location accuracy, process execution success rate, and average process time. And / or, in step S4, the preset index is at least one of the following: fault location accuracy threshold, process execution success rate threshold, and average process time threshold.
4. The method according to claim 1, characterized in that, In step S1, the collected system information includes one or more of the following: system logs, operational alarms, performance indicators, and configuration information. And / or, in step S1, the abnormal event includes at least one of network interruption, buffer full, service process abnormality, data acquisition timeout, or data quality abnormality.
5. The method according to claim 1, characterized in that, In step S2, the graphical configuration interface is a visual logic orchestration interface, which is used to construct a fault analysis process with a sequential order by dragging and dropping fault cause model icons and establishing connection lines.
6. The method according to claim 1, characterized in that, In step S3, the abnormal events associated with the fault cause model in the fault analysis process are verified, including: Based on the correlation in the fault cause model, the corresponding real-time acquisition system information is automatically obtained; Based on the verification rules in the fault cause model, determine whether the corresponding abnormal event has occurred according to the real-time collected system information. If the corresponding abnormal event is determined to have occurred, the corresponding fault location result is output and the process is terminated. If it is determined that none of the abnormal events associated with all fault cause models in the fault analysis process have occurred, an analysis failure indication will be output.
7. A model-based fault analysis device for power control systems, characterized in that, Including processor and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the method according to any one of claims 1 to 6.
8. A model-based power control system for fault acquisition and analysis, characterized in that, include: At least one fault analysis device as described in claim 7; The data acquisition subsystem of the power control system is used to provide information from the data acquisition system; A communication network is used to establish a data interaction link between the fault analysis device and the acquisition subsystem to transmit acquisition system information and fault analysis instructions.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method according to any one of claims 1 to 6.
10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 6.