Electrical work ticket safety measure intelligent checking method based on safety measure knowledge base

Abstract

The invention provides an electrical work ticket safety measure intelligent checking method and device based on a safety measure knowledge base, and electronic equipment. The method comprises the following steps: analyzing a target equipment number and a target operation type from work ticket content of a target power plant in an operation process; searching an equipment search path rule query statement and an equipment safety measure term template corresponding to the target equipment from a safety measure knowledge base according to a target equipment type and a target operation type corresponding to the target equipment number; using the target equipment number as an input parameter of an equipment search path rule query statement, and querying an associated equipment number having an electrical topology connection relationship with the target equipment from a power grid graph database; according to target equipment information corresponding to the target equipment number, associated equipment information corresponding to the associated equipment number, the equipment safety measure term template and the target operation type, generating safety measure content; and intelligently checking the work ticket content according to the safety measure content to obtain the standard electrical work ticket content.

Description

Technical Field

[0001] This application relates to the technical fields of artificial intelligence, power system automation and intelligent operation and maintenance, and more specifically, to a method, device and electronic device for intelligent verification of electrical work order safety measures based on a safety measure knowledge base. Background Technology

[0002] Currently, work permits in the power industry rely on manual compilation, and the design of safety measures depends heavily on the experience of the operators. For example, the power plant's work supervisor lists the safety measures in detail on the work permit, and the permit reviewer verifies, supplements, or corrects it based on procedures, experience, and actual site conditions to ensure comprehensive coverage of potential risks. However, in practice, it has been found that due to the operators' experience level, professional background, and familiarity with the on-site equipment, safety measures are easily omitted or incorrectly written. This makes it difficult to improve the efficiency of power operations based on work permits while ensuring the safety of power plant operations. Summary of the Invention

[0003] The purpose of this application is to provide an intelligent verification method, device, and electronic device for electrical work permit safety measures based on a safety knowledge base, which can improve the efficiency of power operations based on work permits while ensuring the safety of power plant operations.

[0004] This application provides an intelligent verification method for electrical work permit safety measures based on a safety measures knowledge base. The method includes: parsing the target equipment number and target operation type from the work permit content of the target power plant during operation; obtaining the target equipment type corresponding to the target equipment number, and searching the safety measures knowledge base for the corresponding equipment search path rule query statement and equipment safety measures terminology template based on the target equipment type and target operation type. The safety measures knowledge base stores the correspondence between equipment search path rule query statements, equipment safety measures terminology templates, equipment types, and operation types; using the target equipment number as the input parameter of the equipment search path rule query statement, querying the associated equipment number with an electrical topology connection to the target equipment from the power grid diagram database; generating safety measures content based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, the equipment safety measures terminology template, and the target operation type; and intelligently verifying the work permit content based on the safety measures content to obtain standard electrical work permit content. In the implementation of the above scheme, by parsing the target equipment from the work order content of the target power plant during the operation process and searching for its associated equipment from the power grid diagram database, it is possible to ensure that safety measures cover all physical or logically related nodes, avoid omitting key protection objects, and thus ensure the integrity of the work order and the safety of the operation process. Furthermore, based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, the equipment safety measure terminology template, and the target operation type, safety measures content for verifying the work order content is generated, thereby eliminating subjective differences when manually formulated, making the safety measures conform to the established technical specifications, and improving the efficiency of power operations based on work orders while ensuring the safety of the power plant's operation process.

[0005] Optionally, in this embodiment, obtaining the target device type corresponding to the target device number includes: searching for the target device type corresponding to the target device number from the device ledger table, where the device ledger table stores the correspondence between device identifiers and device types. In the implementation of the above scheme, by centrally managing the mapping relationship between device identifiers and device types through a pre-established device ledger table, the overhead of dynamically parsing or calculating the device type for each query is avoided, thus significantly improving the efficiency of device type queries. Especially in large-scale device management scenarios, this centralized search method can reduce system resource consumption. Furthermore, by searching through the direct mapping relationship between device identifiers and device types, complex logical judgments or condition matching processes are eliminated, simplifying the algorithmic complexity of device type identification and making the system more stable and reliable.

[0006] Optionally, in this embodiment, the associated device number includes a primary device number and a secondary device number. Generating safety measures content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety terminology template, and the target operation type includes: querying the primary device number and secondary device number from the power grid diagram database based on the target device number; obtaining the device information corresponding to the primary device number and the device information corresponding to the secondary device number from the device ledger table; and filling the device information corresponding to the primary device number, the device information corresponding to the secondary device number, the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, and the target operation type into the device safety terminology template to obtain the safety measures content. In the implementation of the above scheme, by querying the primary device number and secondary device number from the power grid diagram database and obtaining their corresponding device information, comprehensive identification and integration of the monitoring, control, and protection devices related to the target device are achieved, thereby ensuring the comprehensiveness and accuracy of the safety measures content and avoiding safety hazards caused by the omission of key equipment. Furthermore, by filling the equipment information corresponding to the primary and secondary equipment numbers, target equipment information, associated equipment information, and target operation type into the equipment safety measure terminology template, dynamic integration of multi-dimensional information is achieved, making the generated safety measures more personalized and targeted, and better able to adapt to the needs of different equipment and operation scenarios.

[0007] Optionally, in this embodiment, generating safety measures content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type includes: obtaining the target device information corresponding to the target device number and the associated device information corresponding to the associated device number from the device ledger table; retrieving topological relationship device information between the target device and associated devices using the knowledge graph of the power grid diagram database; generating safety measure prompt engineering text based on the target device information, associated device information, target operation type, device safety measure terminology template, and topological relationship device information; and inputting the safety measure prompt engineering text into a pre-trained language model so that the pre-trained language model generates safety measure content based on the target device information, associated device information, device safety measure terminology template, and target operation type, wherein the safety measure content conforms to the target device type and the target operation type. In the implementation of the above scheme, by combining the device ledger table and the knowledge graph retrieval of the power grid diagram database, accurate identification of the topological relationship between the target device and associated devices is achieved, thereby enabling a more comprehensive consideration of the mutual influence between devices. The generated safety measure content not only targets a single device but also covers the potential risks of associated devices, significantly improving the completeness and accuracy of the safety measures. Furthermore, by using pre-trained language models to generate security measures, the knowledge learned by the models on large-scale data can be fully utilized to automatically adapt to combinations of different device types and operation types, generating highly customized security measures, which significantly improves the flexibility and adaptability of the system.

[0008] Optionally, in this embodiment, intelligent verification of the work order content based on the safety measures includes: comparing the safety measures content with the work order content to obtain a comparison result; obtaining a preset intelligent verification prompt template, and replacing the template variable in the intelligent verification prompt template with the comparison result, the safety measures content, and the work order content to obtain intelligent verification prompt engineering text; inputting the intelligent verification prompt engineering text into a pre-trained language model, so that the pre-trained language model performs intelligent verification of the work order content in the prompt engineering text based on the safety measures content and the comparison result to obtain standard electrical work order content. In the implementation of the above solution, by comparing the safety measures content with the work order content and generating a comparison result, this technical solution can automatically identify the differences and potential conflicts between the two, thereby improving the accuracy and comprehensiveness of the verification and avoiding omissions or errors that may occur during manual verification. Furthermore, by inputting the prompt engineering text into a pre-trained language model for intelligent verification, this technical solution can utilize the model's powerful semantic understanding and reasoning capabilities to automatically generate standard electrical work order content, not only reducing the need for manual intervention but also significantly improving the efficiency and intelligence level of the verification process.

[0009] Optionally, in this embodiment, after obtaining the standard electrical work permit content, the method further includes: determining the work permit completion information of the target equipment during the operation process based on the standard electrical work permit content. In the implementation of the above solution, by directly linking the standard electrical work permit content to the work permit completion information of the target equipment, the verification process and work permit management are automatically integrated, reducing manual intervention and potential omissions or errors, and improving the completeness and accuracy of the work process. Furthermore, by determining the work permit completion information through the standard electrical work permit content, the work permit content can be dynamically adjusted according to the actual operation situation, ensuring that the work permit always remains consistent with the equipment's operating status, thereby improving the real-time performance and adaptability of operation management.

[0010] Optionally, in this embodiment, determining the work order completion information for the target equipment during the operation process based on the content of the standard electrical work order includes: if the equipment number of the target equipment in the work order content is inconsistent with the equipment number in the standard electrical work order content, then the comparison result of the inconsistent equipment number of the target equipment is added to the work order completion information; if the measure terminology of the target equipment in the work order content does not match the measure terminology in the standard electrical work order content, then the comparison result of the mismatch of measure terminology of the target equipment is added to the work order completion information; if the number of associated equipment of the target equipment in the work order content is less than the number of associated equipment in the standard electrical work order content, then the associated equipment in the standard electrical work order content is added to the work order completion information; if the operation sequence in the work order content does not match the operation sequence in the standard electrical work order content, then the operation sequence in the standard electrical work order content is added to the work order completion information. In the implementation of the above solution, by adding the comparison results of inconsistent equipment numbers, mismatched terminology, inconsistent equipment quantities, and mismatched operation sequences to the work order completion information, the safety and reliability of the operation are improved. This automated comparison mechanism reduces the workload of manual verification and reduces the possibility of human error.

[0011] This application embodiment also provides an intelligent verification device for electrical work permit safety measures based on a safety measure knowledge base, including: a number type parsing module, used to parse the target equipment number and target operation type of the target equipment from the work permit content of the target power plant during operation; a query statement lookup module, used to obtain the target equipment type corresponding to the target equipment number, and search for the corresponding equipment search path rule query statement and equipment safety measure terminology template from the safety measure knowledge base according to the target equipment type and target operation type, the safety measure knowledge base stores the correspondence between equipment search path rule query statements, equipment safety measure terminology templates, equipment types and operation types; an associated equipment query module, used to use the target equipment number as the input parameter of the equipment search path rule query statement, and query the associated equipment number that has an electrical topology connection relationship with the target equipment from the power grid diagram database; a safety measure content generation module, used to generate safety measure content based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, the equipment safety measure terminology template and the target operation type; and a content intelligent verification module, used to intelligently verify the work permit content based on the safety measure content to obtain standard electrical work permit content.

[0012] Optionally, in this embodiment of the application, the query statement lookup module includes: a device type lookup submodule, used to look up the target device type corresponding to the target device number from the device ledger table, wherein the device ledger table stores the correspondence between device identifiers and device types.

[0013] Optionally, in this embodiment, the associated device number includes a primary device number and a secondary device number; the safety measure content generation module includes: a secondary device query submodule, used to query the primary device number and the secondary device number from the power grid diagram database according to the target device number; a device information acquisition submodule, used to obtain the device information corresponding to the primary device number and the device information corresponding to the secondary device number from the device ledger table; and a safety measure template filling submodule, used to fill the device information corresponding to the primary device number, the device information corresponding to the secondary device number, the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, and the target operation type into the device safety measure terminology template to obtain the safety measure content.

[0014] Optionally, in this embodiment, the safety measure content generation module includes: an equipment information acquisition submodule, used to acquire target equipment information corresponding to the target equipment number and associated equipment information corresponding to the associated equipment number from the equipment ledger table; a topology relationship retrieval submodule, used to retrieve topology relationship equipment information between the target equipment and associated equipment using the knowledge graph of the power grid diagram database; a template variable replacement submodule, used to generate safety measure prompt engineering text based on the target equipment information, associated equipment information, target operation type, equipment safety measure terminology template, and topology relationship equipment information; and a prompt text input submodule, used to input the safety measure prompt engineering text into a pre-trained language model, so that the pre-trained language model generates safety measure content based on the target equipment information, associated equipment information, equipment safety measure terminology template, and target operation type, wherein the safety measure content conforms to the target equipment type and target operation type.

[0015] Optionally, in this embodiment, the content intelligent verification module includes: a comparison result acquisition submodule, used to compare the safety measure content with the work order content to obtain a comparison result; an engineering text acquisition submodule, used to acquire a preset intelligent verification prompt word template, and replace the template variable in the intelligent verification prompt word template with the comparison result, safety measure content, and work order content to obtain intelligent verification prompt engineering text; and a verification content acquisition submodule, used to input the intelligent verification prompt engineering text into a pre-trained language model, so that the pre-trained language model performs intelligent verification of the work order content in the prompt engineering text based on the safety measure content and the comparison result to obtain standard electrical work order content.

[0016] Optionally, in this embodiment of the application, the intelligent verification device for electrical work permit safety measures based on the safety measures knowledge base further includes: a work permit information improvement module, used to determine the work permit improvement information of the target equipment during the operation process according to the content of the standard electrical work permit.

[0017] Optionally, in this embodiment, the work order information improvement module includes: a first information addition submodule, used to add the comparison result of the discrepancy between the equipment number of the target equipment in the work order content and the equipment number in the standard electrical work order content to the work order improvement information if the equipment number of the target equipment in the work order content is inconsistent with the equipment number in the standard electrical work order content; a second information addition submodule, used to add the comparison result of the mismatch between the measure terminology of the target equipment in the work order content and the measure terminology in the standard electrical work order content to the work order improvement information if the number of associated equipment of the target equipment in the work order content is less than the number of associated equipment in the standard electrical work order content; and a fourth information addition submodule, used to add the operation sequence of the standard electrical work order content to the work order improvement information if the operation sequence in the work order content does not match the operation sequence in the standard electrical work order content.

[0018] This application also provides an electronic device, including a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the machine-readable instructions are executed by the processor to perform the methods described above.

[0019] This application also provides a computer-readable storage medium storing a computer program, which is executed by a processor to perform the methods described above.

[0020] This application also provides a computer program product, including: a computer program or computer instructions, which are executed by a processor to perform the method described above. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The illustration shows a flowchart of the intelligent verification method for electrical work permit safety measures based on a safety measures knowledge base provided in this application embodiment; Figure 2 The diagram shown is a schematic representation of a wiring diagram for constructing a power grid diagram database provided in an embodiment of this application. Figure 3 The diagram shown is a schematic representation of the security measures generated according to an embodiment of this application. Figure 4 The diagram shown illustrates the process of determining the completeness information of the generated work order provided in an embodiment of this application. Figure 5 The diagram shown is a structural schematic of the intelligent verification device for electrical work permit safety measures based on a safety measures knowledge base provided in this application embodiment; Figure 6 The diagram shows a structural schematic of an electronic device provided in an embodiment of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in the embodiments of this application are for illustrative and descriptive purposes only and are not intended to limit the protection scope of the embodiments of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the embodiments of this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of the embodiments of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0024] Furthermore, the described embodiments are merely a part of the embodiments of this application, and not all of them. The components of the embodiments of this application described and illustrated herein can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed embodiments of this application, but merely to illustrate selected embodiments of this application.

[0025] It is understood that the terms "first" and "second" in the embodiments of this application are used to distinguish similar objects. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and that "first" and "second" do not necessarily imply that they are different. In the description of the embodiments of this application, the term "and / or" is merely a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship. The term "multiple" refers to two or more (including two), and similarly, "multiple groups" refers to two or more groups (including two groups).

[0026] It should be noted that the intelligent verification method for electrical work permit safety measures based on the safety measures knowledge base provided in this application can be executed by electronic devices. Here, electronic devices refer to device terminals or servers with the function of executing computer programs. Device terminals include, for example, smartphones, personal computers, tablets, personal digital assistants, or mobile internet devices. Servers refer to devices that provide computing services through a network. Servers include, for example, x86 servers and non-x86 servers. Non-x86 servers include, for example, mainframes, minicomputers, and UNIX servers.

[0027] Currently, work permit management in the power industry relies heavily on manual drafting. Safety measures are often designed by operators (such as the work supervisor at a power plant) based on their experience and on-site judgment. For example, when filling out a work permit, the work supervisor must manually draft key safety clauses such as the outage area, grounding wire location, and isolation measures, taking into account the specific work content, equipment status, and environmental conditions. These clauses are then reviewed, supplemented, or revised by permit reviewers based on regulations, experience, and actual on-site conditions. This process is essentially heavily reliant on manual experience and lacks standardized, automated tools, resulting in the completeness and accuracy of safety measures heavily depending on individual ability. If operators lack sufficient understanding of the regulations or familiarity with the on-site equipment, they may overlook key risks, thus creating potential safety hazards.

[0028] In practice, due to differences in the experience level, professional background, and understanding of on-site equipment among operators, deviations often occur in the writing of safety measures. For example, inexperienced personnel may overlook risks in certain special working conditions (such as the risk of electric shock from nearby live equipment), or incorrectly mark the isolation range due to unfamiliarity with equipment parameters. Furthermore, while work order reviewers can correct problems based on procedures, the subjectivity and efficiency of manual review make it difficult to comprehensively cover potential risks in complex scenarios. This "experience-driven" model not only increases the probability of human error but also leads to lengthy work order approval processes, impacting operational efficiency. Especially in urgent or high-risk operations, the cumbersome manual verification process may delay the start of work or even cause accidents due to inadequate measures.

[0029] This demonstrates that the manual work order creation model has inherent flaws: first, reliance on individual experience easily leads to omissions or errors in safety measures; second, the lack of systematic risk identification tools makes it difficult to dynamically adapt to complex operational scenarios; and third, the inefficient manual review process restricts operational efficiency. Therefore, currently in the power industry, it is difficult to improve the efficiency of power operations based on work orders while ensuring the safety of power plant operations.

[0030] Please see Figure 1The illustrated flowchart illustrates an intelligent verification method for electrical work permit safety measures based on a safety measures knowledge base, provided in this application embodiment. The main idea of ​​this method is to parse the target equipment from the work permit content of the target power plant during operation and search for its associated equipment in the power grid diagram database. This ensures that safety measures cover all physical or logically related nodes, avoiding omissions of critical protection objects, thereby guaranteeing the integrity of the work permit and the safety of the operation process. Furthermore, safety measures content for verifying the work permit content is generated based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, the equipment safety measures terminology template, and the target operation type. This eliminates subjective differences during manual formulation, ensuring that the safety measures comply with established technical specifications. While guaranteeing the safety of the power plant's operation process, this improves the efficiency of power operations based on work permits. The implementation methods of the aforementioned intelligent verification method for electrical work permit safety measures based on a safety measures knowledge base may include: Step S110: Extract the target equipment number and target operation type from the work order content of the target power plant during the operation process.

[0031] The target power plant refers to a specific power plant for which operations need to be carried out. Its equipment and work order contents are the objects of this technical solution, such as thermal power plants, hydropower plants, nuclear power plants, etc.

[0032] A work permit is a formal document used to record and authorize work performed during operations at a power plant. Examples include electrical work permits, thermal machinery work permits, and work permits for working at heights. For ease of understanding and explanation, this application will use electrical work permits as the primary reference. An electrical work permit is a standardized safety operation document used by a power plant during equipment inspection, maintenance, and other operations. It includes the equipment being worked on, the type of operation, and safety measures. The work permit may include information about the target equipment, such as the equipment number and the type of operation required.

[0033] The target equipment is the power plant equipment specified in the work order that needs to be operated, such as transformers, circuit breakers, generators, disconnect switches, grounding wires, grounding switches, etc. This target equipment can be manufactured by power equipment manufacturers and introduced into the power plant through procurement and installation.

[0034] The target device number is a unique identifier for the target device, used to accurately locate the device in the system. For example, "TR-001" represents transformer No. 1, and "CB-002" represents circuit breaker No. 2.

[0035] The target operation type is the category of operation to be performed on the target equipment as specified in the work order. For example, it may be the inspection, maintenance, replacement, or testing of circuit breakers (switches) or disconnectors (knife switches). The specific type is determined by the person filling out the work order based on the actual work requirements, or it may be submitted to the server system by the person filling out the work order.

[0036] Step S120: Obtain the target device type corresponding to the target device number, and search for the corresponding device search path rule query statement and device safety measure terminology template from the safety measure knowledge base according to the target device type and target operation type. The safety measure knowledge base stores the correspondence between device search path rule query statements, device safety measure terminology templates, device types and operation types.

[0037] The target device type is the device category to which the target device belongs. This target device type can be used to find the device lookup path rules corresponding to the target device.

[0038] A safety measure knowledge base refers to a knowledge base that stores query statements for device lookup paths, templates for device safety measure terminology, and the correspondence between device types and operation types. For example, it can be a query rule table in a relational database, containing fields such as device type, operation type, and query statements (such as Cypher or Gremlin query statements in a power grid diagram database).

[0039] Step S130: Using the target device number as the input parameter of the device lookup path rule query statement, query the associated device numbers that have an electrical topology connection with the target device from the power grid diagram database.

[0040] Device path rule lookup statements are specific query commands used to find path rules between devices in a power grid diagram database. Examples include Cypher or Gremlin queries for power grid diagram databases. These statements are typically written by database experts based on the type of graph database and the query requirements.

[0041] Graph databases are databases that store data using a graph structure to represent the electrical connections between devices. Specific examples include Neo4j, ArangoDB, and TigerGraph. In a power grid graph database, nodes represent devices, and each node's attributes include device number, coordinate location, and device type. Edges between nodes represent the electrical connections between devices. Power grid graph databases possess powerful pathfinding and traversal algorithms, enabling intelligent verification systems to intelligently identify all associated device information related to the target device to be inspected.

[0042] Electrical topology is the network connection between power plant equipment through electrical lines, such as the connection between transformers and circuit breakers, or the connection between busbars and other equipment. This electrical topology can be obtained through the digital conversion of power plant electrical design drawings.

[0043] The associated device number is a unique identifier for other devices that are electrically connected to the target device, such as the circuit breaker number or disconnector number connected to the transformer. This associated device number can be obtained by querying the adjacent nodes of the target device through the power grid database.

[0044] Step S140: Generate safety measures content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type.

[0045] Safety measures are the safety protections and operating procedures required for specific operations, such as disconnecting the power supply and testing for electricity, hanging warning signs, and setting up temporary fences. These safety measures can be automatically generated by the system based on the target equipment information, associated equipment information, and target operation type.

[0046] Understandably, the aforementioned safety measures can be categorized into three types: equipment isolation operations, grounding protection operations, and safety protection operations. Equipment isolation operations, for example, require the operation of circuit breakers (switches) and disconnectors (knife switches), and the dual equipment identification numbers must be clearly stated (e.g., "11BBA30 Bay 01 Booster Circuit Breaker"). Grounding protection operations, for example, require the installation of grounding wires and the closing of grounding disconnectors, and the installation location and dual equipment names must be clearly marked. Safety protection operations, for example, require the installation of barriers, the hanging of signs (e.g., "Do Not Close, People Working"), and the hanging of "In Operation" red banners in adjacent operating bays, and the protection targets and their coordinates must be clearly stated. In the implementation of the above scheme, by automatically parsing the target equipment number and operation type from the work order content, and combining the topology query capabilities of the safety measures knowledge base and the power grid diagram database, accurate identification of complex connections between electrical equipment is achieved, significantly improving the accuracy and comprehensiveness of safety measures formulation. This automated processing method based on structured data eliminates the subjectivity and risk of omission in manual verification, fundamentally solving the problem that traditional manual verification is difficult to cover complex electrical topology relationships.

[0047] Step S150: Perform intelligent verification of the work order content based on the safety measures to obtain the standard electrical work order content.

[0048] The standard electrical work order content is the result of verification and supplementation by an intelligent system. For example, it might include work orders that have added missing safety measures or corrected erroneous equipment information. Understandably, by organically combining equipment information, topology relationships, and operation type for intelligent verification, a closed-loop verification of the work order content is achieved. This multi-dimensional cross-verification mechanism not only identifies obvious safety measure deficiencies but also uncovers potential topology-related risks, significantly improving the safety protection level of electrical operations. The entire verification process described above achieves fully automated processing from data parsing to measure generation, significantly improving work efficiency. By eliminating manual intervention, it reduces human resource consumption and avoids human error, achieving an order-of-magnitude increase in processing speed while ensuring verification quality.

[0049] In the implementation of the above scheme, by parsing the target equipment from the work order content of the target power plant during the operation process and searching for its associated equipment from the power grid diagram database, it can be ensured that safety measures cover all physical or logical associated nodes, avoiding omission of key protection objects, thereby ensuring integrity and safety of the operation process. Furthermore, based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, the equipment safety measure terminology template, and the target operation type, safety measures content for verifying the work order content is generated, thereby eliminating subjective differences when manually formulated, making the safety measures conform to the established technical specifications, and improving the efficiency of power operations based on work orders while ensuring the safety of the power plant's operation process.

[0050] As an optional implementation of step S110 above, the implementation of obtaining the target equipment type corresponding to the target equipment number may include: parsing the target equipment number from the work order content of the target power plant during operation; after parsing the target equipment number, searching for the target equipment type corresponding to the target equipment number in the equipment ledger table of relational data, since the equipment ledger table stores the correspondence between equipment identifiers and equipment types. In the implementation of the above scheme, by using a standardized equipment ledger table to store equipment type information, the uniformity and consistency of equipment type data are ensured, avoiding equipment type identification errors caused by scattered storage or data inconsistencies between different systems, thus improving the accuracy of equipment management. Furthermore, the structured design of the above equipment ledger table makes the maintenance and updating of equipment type information more convenient; only the correspondence in the ledger table needs to be modified to achieve global effect, without modifying multiple code or configurations, reducing the complexity of system maintenance.

[0051] It is understandable that extracting the target equipment numbers of entities such as circuit breakers, disconnectors, grounding wires, and grounding switches from the work order content during the operation of the target power plant is to achieve precise location and information association for specific equipment. Work orders typically contain key information such as equipment name, number, and location, but manual filling or descriptions may contain ambiguities or inconsistencies (such as the use of non-standardized abbreviations). By parsing the target equipment number, it can be converted into a unified and standardized identifier (such as KKS coding), thereby interfacing with the power plant's internal equipment management system. This process not only eliminates ambiguity in human expression but also provides basic data support for subsequent automated operations (such as risk assessment and safety measure matching), ensuring the accuracy and traceability of the work process. Furthermore, operation status keywords and target operation statuses can be identified from the work order content. For example, a triplet can be constructed based on the identified equipment-operation-status information, such as {Equipment: 11BBA30 Circuit Breaker, Operation: Open, Status: Isolated}.

[0052] After parsing the target equipment number, the corresponding target equipment type is looked up in the equipment ledger table of the relational database. This is because the equipment ledger table is essentially a mapping table between equipment identifiers and attributes. For example, according to KKS coding rules, the equipment number already implicitly contains information such as equipment category and functional area (e.g., "T" represents transformer, "P" represents pump), and the ledger table further stores these codes and equipment types (e.g., "220kV main transformer" "circulating water pump") in a structured manner. By querying the ledger table, the physical characteristics, operating parameters, and maintenance requirements of the equipment can be quickly obtained, thus providing a basis for the design of safety measures in the work order (e.g., power outage scope, isolation method). This automated processing method based on data association reduces reliance on human experience and improves the standardization and safety of the work process.

[0053] Optionally, as an alternative implementation of step S120 above, for example, the target device type corresponding to the target device number is obtained through the Device Master Table in a relational database. The Device Master Table typically uses the device number as a unique identifier and stores the basic attributes of the device (such as device type, installation location, technical parameters, etc.). Specifically, the target device number parsed from the work order can be associated with the Device Master Table through SQL JOIN operations or subqueries. For example, if the target device number is "KKS-1234", a query similar to the following can be executed: SELECT device_type FROM device_master WHERE device_id = 'KKS-1234'. This query directly matches the device type (such as "220kV circuit breaker") through the device number, thereby clarifying the physical characteristics and operational constraints of the device. This structured storage method ensures the uniqueness and traceability of device type information, avoiding deviations that may be caused by manual experience judgment.

[0054] Then, based on the target device type and target operation type, the system searches the Anco Knowledge Base for the corresponding device lookup path rule query statement. The Anco Knowledge Base stores the correspondence between device lookup path rule query statements, device types, and operation types. This Anco Knowledge Base (Association Rule Table) is a predefined rule base. Its core logic is to use device type (e.g., "circuit breaker") and operation type (e.g., "power outage maintenance") as input conditions to match the corresponding device lookup path rule query statement (e.g., "SELECT * FROM connected_devices WHERE device_type = 'grounding switch' AND location = 'control room'"). The table is designed based on standardized power operation procedures and historical experience, achieving efficient matching through the following mechanism: the fields of the Anco Knowledge Base contain the mapping relationship between device type, operation type, and device lookup path rule query statement. For example, when the device type is "circuit breaker" and the operation type is "power outage maintenance," the device lookup path rule query statement is designed to retrieve all grounding switches or disconnect switches connected to that circuit breaker. The system performs conditional matching (e.g., WHERE device_type = 'circuit breaker' AND operation_type = 'power outage maintenance') in the safety measures knowledge base based on the combination of target equipment type and operation type, and extracts the corresponding query statement. This predefined rule avoids complex real-time calculations and improves query efficiency. The content of the safety measures knowledge base needs to be updated regularly to adapt to new equipment types or operation scenarios. For example, when adding rules for new energy equipment (such as photovoltaic inverters), industry standards and historical accident cases need to be combined to ensure that the query statement covers all potentially risky equipment. The essence of the safety measures knowledge base is to make implicit experience in power operations explicit, and through structured data storage and conditional matching, to achieve automation and precision in safety measure verification.

[0055] Please see Figure 2The illustration shows a schematic diagram of a wiring diagram for constructing a power grid diagram database provided in an embodiment of this application. It is understood that the electrical topology connections in the power grid diagram database can be constructed from wiring diagrams drawn based on field wiring conditions. For example, field wiring methods are typically displayed using wiring diagrams. These diagrams clearly identify each device and clearly label the various devices and their connections, with accurate representation of the connections. Therefore, by performing topology analysis on the wiring diagrams, the electrical devices and their topology connections can be extracted, transforming the field wiring diagrams into graph data models with topology attributes. These graph data models include the electrical devices and their topology connections. Finally, the graph data model is imported into the aforementioned power grid diagram database, thereby transforming the unstructured data of the electrical device wiring diagrams into structured topology connections in the power grid diagram database.

[0056] This topology connection includes the physical connections of devices such as transformers, circuit breakers, trolleys, disconnectors, and busbars. Each device node contains a unique identifier (e.g., elementid), coordinates (x, y), and device type label (e.g., "circuit breaker" or "grounding switch"). The electrical equipment and the topology connections between them are then stored in the power grid diagram database, thus obtaining the electrical topology connections in the power grid diagram database.

[0057] Optionally, as an alternative implementation of step S130 above, for example: using the target device number as the input parameter of the device search path rule query statement, the system queries the power grid database for associated device numbers that have an electrical topological connection with the target device. The power grid database is stored with devices as nodes and electrical connections between devices as edges. Each node's attributes include device number, coordinate location, and device type. During the query process in the power grid database, the system can start from the device node corresponding to the target device number. For example, the target device number can be used as the input parameter of the device search path rule query statement, and the system uses the shortest path algorithm (Dijkstra's algorithm) to query the power grid database for associated device numbers that have an electrical topological connection with the target device. Specifically, when searching for "11BBA30 circuit breaker", the system automatically associates devices such as disconnectors, handcart switches, grounding disconnectors, and cabinet doors on both sides of the target device. The associated devices retrieved for the target device "11BBA30 circuit breaker" can contain 191 nodes, while the associated devices retrieved based on the topological relationship between the two can contain 188 related devices.

[0058] Please see Figure 3The diagram illustrates the generated safety measures content provided in the embodiments of this application. Another optional implementation of step S130 above is as follows: Taking switchgear maintenance as an example, assuming the task is to search for associated equipment in the power grid database for the "11BBA30 bay 01 booster circuit breaker" of the switchgear, the system can first search for the obvious disconnection point of the circuit breaker on the switchgear (the disconnectors or trolleys on both sides of the circuit breaker) in the power grid database. Then, it can search for the front and rear gates of the switchgear in the power grid database. Finally, it can search for the grounding point and grounding disconnector connected to the switchgear in the power grid database. After the work order filler inputs "11BBA30 bay 01 booster circuit breaker" into the intelligent verification system, the intelligent verification system can generate safety measures content based on the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, and the target operation type, etc., found in the query for "11BBA30 bay 01 booster circuit breaker". It can be understood that by using the power grid database to store equipment topology relationships and combining the dynamic matching of equipment attribute information and equipment search path rule query statements, intelligent generation of electrical safety measures is achieved. This technical solution breaks through the traditional verification mode based on fixed rules, and can dynamically adapt to the needs of different equipment types and operating scenarios, making the security measures highly targeted and scalable.

[0059] The above safety measures may include: (1) Circuit breakers and disconnecting switches should be disconnected, including circuit breakers and disconnecting switches that have been disconnected before filling in (indicate the number), and fuses should be removed, including: 1. Disconnecting the circuit breaker of the 11BBA30 bay 01 booster; 2. Pulling the trolley switch of the 11BBA30 bay 01 booster to the test position; 3. Opening the control power supply of the trolley switch of the 11BBA30 bay 01 booster; 4. Opening the closing power supply of the trolley switch of the 11BBA30 bay 01 booster. (2) Grounding wires, partitions, and isolation devices should be installed (indicate the exact location), and grounding switches should be closed (indicate the dual name), including: 1. Closing the grounding switch of the 11BBA30 bay 01 booster. (3) Measures such as setting up barriers, hanging signs, and hanging red cloth banners with the word "In Operation" on adjacent operating bays should be taken, including: 1. Hanging a sign that reads "Do Not Close, People Working" on the trolley switch of the booster 01 in bay 11BBA30; 2. Hanging a sign that reads "Do Not Operate, People Working" on the front cabinet door of the booster 01 in bay 11BBA30; 3. Hanging a sign that reads "Do Not Operate, People Working" on the rear cabinet door of the booster 01 in bay 11BBA30.

[0060] As an optional implementation of step S140 above, the associated device number may include a primary device number and a secondary device number; the implementation of generating safety measure content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type may include: Step S141: Query the primary equipment number and secondary equipment number from the power grid diagram database based on the target equipment number.

[0061] A primary device number refers to the device number that is directly physically connected to the main device and can conduct current through this connection.

[0062] Secondary equipment number refers to the number of protection, measurement, and control equipment associated with the main equipment. For example, "PT-101" is the protection device for main transformer No. 1, and "CT-205" is the current transformer for circuit breaker No. 205. This type of secondary equipment number can be installed as part of the main equipment, and the number is usually associated with the main equipment number.

[0063] Understandably, the power grid graph database can employ an intelligent processing engine driven by the power grid graph database to implement a dual-engine architecture for graph model topology analysis, knowledge base rule matching, as well as functions such as device association analysis and security measure content verification.

[0064] The implementation of step S141 above can be exemplified as follows: Starting from the device node corresponding to the target device number to be inspected, the primary and secondary device numbers are queried from the power grid graph database using a shortest path algorithm (such as Dijkstra's algorithm) based on the target device number. It is understood that querying the primary and secondary device numbers in the power grid graph database using the target device number is based on the complex relationships between devices in a power system. The aforementioned power grid graph database (such as Neo4j) stores devices and their connections in the form of nodes and edges, enabling efficient retrieval of monitoring, control, or protection devices (such as relay protection devices and measurement and control units) directly associated with the target device. For example, if the target device is a "220kV circuit breaker," the power grid graph database can quickly return the numbers of secondary devices connected to it, such as "current transformers" or "protection panels." This process leverages the adjacency query advantage of graph structures, avoiding the complexity of multi-table JOINs in traditional relational databases, significantly improving the efficiency and accuracy of associated device retrieval, and providing a complete device association view for subsequent safety measure design.

[0065] Step S142: Obtain the equipment information corresponding to the primary equipment number and the equipment information corresponding to the secondary equipment number from the equipment ledger table.

[0066] An example of implementing step S142 above is as follows: The equipment ledger table, as the core data source, stores standardized attributes of all equipment (such as equipment type, installation location, technical parameters, etc.). Therefore, by obtaining the equipment information corresponding to the primary equipment number and the equipment information corresponding to the secondary equipment number from the equipment ledger table, it can be ensured that the design of subsequent safety measures is based on real and consistent data. For example, assuming the secondary equipment number is "CT-01", the ledger table can provide its equipment type ("current transformer"), rated current ("1000 / 5A"), and installation location ("main control room zone 12"). This acquisition of structured data not only eliminates the subjectivity of human experience judgment but also provides a quantitative basis for isolation ranges, verification conditions, etc. in safety measures, thereby reducing risk omissions caused by missing or incorrect information.

[0067] Step S144: Fill the equipment information corresponding to the primary equipment number, the equipment information corresponding to the secondary equipment number, the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, and the target operation type into the equipment safety measure terminology template to obtain the safety measure content.

[0068] The implementation of step S144 above is as follows: The equipment information corresponding to the primary equipment number, the equipment information corresponding to the secondary equipment number, the target equipment information corresponding to the target equipment number (e.g., matching circuit breaker type in an equipment relationship diagram), the associated equipment information corresponding to the associated equipment number, and the target operation type are filled into the equipment safety measure terminology template to obtain the safety measure content. It can be understood that filling the equipment information corresponding to the primary equipment number, the secondary equipment information, the target equipment information, the associated equipment information, and the operation type into the equipment safety measure terminology template constitutes a logical closed loop for ultimately generating specific safety measure content. For example, the template field "Protective devices to be disconnected" can be dynamically replaced with the equipment information corresponding to the primary equipment number obtained from the ledger or the name of the secondary equipment (e.g., "CT-01 current transformer"), while the "Working area" field is automatically filled in based on the installation location of the associated equipment number (e.g., "GIS-02 disconnector"). This process achieves dynamic generation of safety measures through parameterized templates, ensuring consistency between the content and the on-site equipment while avoiding the inefficiency and errors caused by manual item-by-item writing. The resulting safety measures not only comply with regulations but can also be directly used for operational guidance, significantly improving the safety and efficiency of power operations. In implementing this solution, the combined use of equipment ledgers and power grid diagram databases not only improved the efficiency of equipment information acquisition but also ensured the real-time nature and consistency of the information. This provided a reliable data foundation for generating safety measures and enhanced the stability and reliability of the entire system.

[0069] As an optional implementation of step S140 above, the implementation of generating safety measure content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type may include: Step S145: Obtain the target equipment information corresponding to the target equipment number and the associated equipment information corresponding to the associated equipment number from the equipment ledger table.

[0070] The implementation of step S145 above is as follows: Obtaining the target device information corresponding to the target device number and the associated device information corresponding to the associated device number through the Device Master Table is the foundation for achieving standardization and correlation of device information. As a core data table in a relational database, the Device Master Table uses the device number (such as a KKS code) as a unique identifier and stores attributes such as device type, technical parameters, and installation location. For example, the complete information of the target device and associated devices can be quickly obtained through the SQL query statement: SELECT * FROM device_master WHERE device_id IN ('target device number', 'associated device number'); This process transforms device information from unstructured text descriptions into structured data, providing accurate data input for subsequent topology analysis and security measure generation. The standardized design of the Device Master Table avoids the subjectivity of human experience judgment, ensuring the consistency and traceability of device information.

[0071] Step S146: Use the knowledge graph of the power grid database to retrieve the topological relationship device information between the target device and associated devices.

[0072] Topology-related device information is structured data describing the electrical connections between devices, such as lists of upstream and downstream connected devices or electrical distance information. This topology-related device information can be retrieved by querying a power grid diagram database and is used to reflect the actual electrical wiring relationships.

[0073] For example, the implementation of step S146 above involves a power grid graph database storing topological relationships (such as electrical connections and physical adjacencies) between devices through a knowledge graph, enabling efficient retrieval of device relationships in complex networks. For instance, in a power system, a target device (such as a "220kV circuit breaker") may have direct or indirect electrical connections with associated devices (such as "grounding switches" or "disconnect switches"). Using a query statement in the power grid graph database (such as Cypher syntax): `MATCH (d1:Device{id: "target device number"})-[:CONNECTED_TO]->(d2:Device) RETURN d2;`, the topological path and intermediate device information between the target device and associated devices can be dynamically obtained. The advantage of the power grid graph database lies in its efficient traversal capability of complex relationships. Compared to the multi-table JOIN operations of traditional relational databases, it significantly reduces response time and improves query accuracy. This capability ensures that safety measures are designed to cover all potentially risky devices, avoiding safety hazards caused by omissions in topological relationships.

[0074] Step S147: Generate a safety measure prompt engineering text based on the target device information, associated device information, target operation type, device safety measure terminology template, and topology relationship device information.

[0075] An example of implementing step S147 above is as follows: The aforementioned equipment safety terminology template is a structured text framework that dynamically fills in specific information through predefined variables (such as {target equipment type}, {operation type}) to generate semantically compliant prompt text. For example, the template may contain the following content: "For operation of {target equipment type} of {operation type}, the following safety measures must be performed: 1. Disconnect the {topological relationship equipment} between {target equipment} and {associated equipment}; 2. Install {safety measure type} at the {location} of {target equipment}". By replacing the template variables in the equipment safety terminology template with target equipment information, associated equipment information, operation type, and topological relationship data, the system can generate logically coherent and semantically clear prompt engineering text. This process not only reduces the complexity of manually writing prompts but also ensures a high degree of consistency between the generated content and power industry standards (such as the "Power Safety Work Regulations"), providing a clear input context for the pre-trained language model.

[0076] Step S148: Input the safety measure prompt engineering text into the pre-trained language model so that the pre-trained language model can generate safety measure content that conforms to the target equipment type and target operation type based on the target equipment information, associated equipment information, equipment safety measure terminology templates and target operation type.

[0077] Pre-trained language models are artificial intelligence models used to generate and verify security measure texts. They can be GPT series models or BERT models, etc.

[0078] Prompt engineering text is structured input text designed to guide a pre-trained language model to generate specific outputs, such as safety measure generation prompt templates or work order verification prompt templates.

[0079] The implementation of step S148 above is as follows: The pre-trained language model (such as the GPT series model or the BERT model) learns from a large-scale corpus and has the ability to understand the implicit relationships between equipment type, operation type, and safety measures. When the input prompt engineering text is received, the model combines contextual logic, industry standards, and historical cases to generate safety measures content that conforms to the target equipment type and operation type. For example, for the operation of "220kV circuit breaker power outage maintenance", the model can output the following: 1. Disconnect the isolating switches on both sides of the circuit breaker and lock the operating mechanism; 2. Install grounding wires on both sides of the circuit breaker to ensure no reverse power supply risk; 3. Verify whether the grounding wire resistance value meets the standard (≤0.5Ω). The core of the above steps lies in the deep integration of structured data (equipment information, topology relationships) and natural language by the model, which not only retains the professional requirements of the power industry, but also significantly improves the efficiency and accuracy of safety measure writing through automated generation. Finally, the system transforms manual experience rules into reusable intelligent processes, realizing the standardization and intelligence of safety measure design.

[0080] As an optional implementation of step S150 above, the above-described implementation of intelligently verifying the work order content based on the security measures may include: Step S151: Compare the safety measures with the work order to obtain the comparison results.

[0081] The implementation of step S151 above includes, for example, comparing the safety measures with the work order to identify differences or potential risks, thereby ensuring that the safety measures in the work order cover all necessary operational requirements. For instance, if the safety measures explicitly require "disconnecting the target device from the associated device," but the work order does not mention the specific disconnection location or device number, the comparison result will mark this omission. This comparison process is essentially a cross-validation of structured data (such as device type, operation type) and unstructured text (such as work order description), and its core objective is to discover missing items due to human negligence or lack of experience through data consistency verification.

[0082] Step S152: Obtain the preset intelligent verification prompt template, and replace the template variables in the intelligent verification prompt template with the comparison results, safety measures content and work order content to obtain the intelligent verification prompt engineering text.

[0083] The implementation of step S152 above is as follows: The preset intelligent verification prompt template is a structured framework that integrates the comparison results, safety measures content, and work order content into input text that the model can understand through variable substitution. For example, the template may contain the following: "The known work order content is "{work order content}", the comparison result is "{comparison result}", and the safety measure requirement is "{safety measure content}". Please check the following questions: 1. Does the work order omit the "{missing item}" required in the safety measures? 2. Does the "{redundant item}" in the work order conflict with the safety measures? By replacing the template variables with actual data, the system generates logically clear and semantically complete prompt engineering text. This process requires the pre-trained language model to understand the context and generate output based on rules or learned knowledge. The template design needs to take into account both the professional terminology of the power industry (such as "grounding wire installation location" and "isolation range") and the expression habits of natural language to ensure that the model can accurately parse the input content and generate verification suggestions. In the implementation of the above scheme, by using preset security measure prompt word templates and template variable replacement technology, structured prompt engineering text can be generated quickly and dynamically. This not only improves the data quality input to the pre-trained language model, but also ensures that the generated security measure content has a consistent format and logic, reducing the need for manual intervention. Furthermore, it ensures that the information input to the pre-trained language model has consistency and standardization, thereby improving the model processing efficiency and the reliability of the verification results.

[0084] Step S153: Input the intelligent verification prompt engineering text into the pre-trained language model so that the pre-trained language model can intelligently verify the work order content in the prompt engineering text based on the safety measures content and comparison results, and obtain the standard electrical work order content.

[0085] The standard electrical work permit content is a standardized work permit output after being verified by an intelligent system. It can be automatically generated by comparing the original work permit with the generated safety measures.

[0086] The implementation of step S153 above is as follows: The pre-trained language model receives the prompt engineering text and, combined with its internally stored language knowledge and power industry rules, intelligently verifies the work order content. For example, when the prompt text indicates that "the grounding wire installation location is not specified in the work order," the model will deduce specific correction suggestions (such as "add a set of grounding wires to both sides of equipment A and B") based on the safety measure rule that "the grounding wire must be installed on both sides of the equipment." This process not only verifies the completeness of the work order but also provides an operable improvement scheme, significantly improving the verification efficiency and accuracy. In the implementation of the above scheme, by integrating the target equipment information, associated equipment information, target operation type, and topological relationship equipment information into the prompt engineering text, the pre-trained language model can generate safety measures based on multi-dimensional contextual information, thereby avoiding security vulnerabilities caused by missing information in traditional methods and enhancing the pertinence and reliability of safety measures. Furthermore, by combining the knowledge graph retrieval of the equipment ledger and the power grid diagram database, the topological relationship between the target equipment and related equipment can be accurately identified. This allows for a more comprehensive consideration of the mutual influence between equipment, and the generated safety measures not only target individual equipment but also cover the potential risks of related equipment, significantly improving the completeness and accuracy of the safety measures.

[0087] As an optional implementation of the above-mentioned intelligent verification method for electrical work permit safety measures based on the safety measures knowledge base, after obtaining the content of the standard electrical work permit, it may further include: Step S160: Determine the work order completion information for the target equipment during the operation process based on the standard electrical work order content.

[0088] An optional implementation of step S160 above is as follows: During the process of determining the work order completion information for the target equipment during operation based on the verification ticket content, a four-dimensional comparison verification method can be used to complete the work order content according to the standard electrical work order content, thereby obtaining the work order completion information for the target equipment during operation. Specifically, the four-dimensional comparison verification method includes: First-dimensional comparison verification, for example, comparing the standard terminology in the standard electrical work order content with the input terminology in the work order content. For example, "open the handcart power supply" should match "open the handcart control power supply and close the circuit breaker power supply," thereby verifying the terminology standardization of the work order content. Second-dimensional comparison verification, for example, comparing and correcting the standard number in the standard electrical work order content with the input number in the work order content. When the comparison results for "11BBA300 grounding switch" and "11BBA30 grounding switch" are inconsistent, "11BBA300 grounding switch" needs to be corrected to "11BBA30 grounding switch," thereby verifying the consistency of the equipment number in the work order content. The third-dimensional comparison and verification method includes, for example, performing path analysis on the standard electrical work order content in the power grid diagram database, obtaining the analysis results, and checking whether the operations of related equipment in the work order content are omitted (e.g., automatic prompting if the grounding switch is not operated), thereby performing topology integrity verification on the work order content. The fourth-dimensional comparison and verification method includes, for example, comparing the standard operation sequence in the standard electrical work order content with the input operation sequence in the work order content, obtaining the comparison result, and then verifying whether the operation sequence in the work order content complies with safety regulations (e.g., "disconnect the circuit breaker before pulling the disconnect switch") based on the comparison result, thereby performing safety logic verification on the work order content.

[0089] In implementing the above solution, a closed-loop feedback mechanism is formed by linking the standard electrical work order with the work order completion information. This ensures that any changes or problems during the work process are promptly reflected in the work order, enhancing the traceability and controllability of the work process. Furthermore, by automatically determining the work order completion information, the workload of manual filling and verification is reduced, lowering labor and time costs while improving the efficiency of the work process, making the entire operation more efficient and smooth.

[0090] Please see Figure 4 The diagram shown illustrates the process of determining the work order completion information generated according to an embodiment of this application. As an optional implementation of step S160 above, the implementation of determining the work order completion information of the target equipment during operation based on the content of a standard electrical work order may include: Step S161: If the equipment number of the target equipment in the work order content is inconsistent with the equipment number in the standard electrical work order content, the comparison result of the inconsistency of the equipment number of the target equipment is added to the work order improvement information.

[0091] For example, in implementing step S161 above: Suppose the work order content is "Close the grounding switch of the 11BBA300 bay 01 booster unit," while the standard electrical work order content is "Close the grounding switch of the 11BBA30 bay 01 booster unit." The equipment number of the target equipment in the work order content (i.e., 11BBA300) is inconsistent with the equipment number in the standard electrical work order content (i.e., 11BBA30). The comparison result of the inconsistent equipment number can be added to the work order completion information. The corresponding completion item in the work order completion information could be "Secondary equipment matching for bay equipment failed, equipment number inconsistent: Close the grounding switch of the 11BBA30 bay 01 booster unit." In implementing the above scheme, by adding the comparison result of the inconsistent equipment number to the work order completion information, the accuracy of the target equipment identification can be ensured, avoiding misoperation or equipment confusion caused by incorrect equipment numbering, thereby improving the safety and reliability of the operation. This automated comparison mechanism reduces the workload of manual verification and lowers the possibility of human error.

[0092] Step S162: If the terminology for measures in the work order for the target equipment does not match the terminology for measures in the standard electrical work order, the comparison result of the mismatch between the terminology for measures of the target equipment is added to the work order improvement information.

[0093] For example, the implementation of step S162 above can be described as follows: Suppose the work order content is "Disconnect the circuit breaker of the 11BBA30 bay 01 booster compressor; pull the 11BBA30 bay 01 booster compressor trolley switch to the test position", while the standard electrical work order content is "Disconnect the circuit breaker of the 11BBA30 bay 01 booster compressor; pull the 11BBA30 bay 01 booster compressor trolley switch to the test position; turn on the control power of the 11BBA30 bay 01 booster compressor trolley switch; turn on the closing power of the 11BBA30 bay 01 booster compressor trolley switch", then the comparison result of the mismatch of the measure terms of the target equipment can be added to the work order improvement information. The corresponding improvement item content in the work order improvement information can be "Bay equipment secondary equipment matching failure, terminology omission: turn on the control power of the 11BBA30 bay 01 booster compressor trolley switch; turn on the closing power of the 11BBA30 bay 01 booster compressor trolley switch". In the implementation of the above scheme, the comparison results of mismatched terminology in the work order improvement information can ensure the consistency and standardization of the description of work measures, avoid misunderstandings or execution deviations caused by differences in terminology, improve the clarity of work instructions, and thus improve the accuracy and efficiency of work execution.

[0094] Step S163: If the number of associated devices of the target device in the work order content is less than the number of associated devices in the standard electrical work order content, then add the associated devices in the standard electrical work order content to the work order completion information.

[0095] For example, in implementing step S163 above: assuming the target device has 5 associated devices in the work order content and 10 associated devices in the standard electrical work order content, it is clear that the number of associated devices (5) in the target device's work order content is less than the number of associated devices (10) in the standard electrical work order content. Therefore, the associated devices in the standard electrical work order content can be added to the work order completion information. In implementing the above scheme, by adding the associated devices from the standard electrical work order content to the work order completion information, missing associated device information in the work order can be supplemented, ensuring that all relevant devices are considered during the operation, avoiding safety hazards or operational interruptions caused by missing associated devices. This process enhances the comprehensiveness and completeness of the operation.

[0096] Step S164: If the operation sequence in the work order does not match the operation sequence in the standard electrical work order, then add the operation sequence in the standard electrical work order to the work order completion information.

[0097] An example implementation of step S164 above involves comparing the standard operating sequence in the standard electrical work order with the input operating sequence in the work order content to obtain a comparison result. Then, based on this comparison result, the operation sequence in the work order content is verified to ensure it complies with safety regulations (e.g., "disconnect the circuit breaker before pulling the disconnect switch"). If the operation sequence in the work order content does not match the standard electrical work order content, the operation sequence in the standard electrical work order content is added to the work order completion information, thereby performing a safety logic check on the work order content. In the implementation of the above scheme, by adding the operation sequence from the standard electrical work order content to the work order completion information, potential errors in the operation sequence in the work order can be corrected, ensuring the logic and rationality of the work steps. This process optimizes the work flow and reduces the risk of time waste or equipment damage due to improper operation sequences.

[0098] Optionally, after obtaining the work order completion information, the work order completion information can also be visualized, for example, by highlighting the following content through the front-end interface: Green highlighting: Correct safety measures that match the safety terminology knowledge base; Yellow highlighting: Missing safety measures that need to be added (such as "open the handcart and close the power supply"); Red highlighting: Errors in safety measures that need to be corrected (such as incorrect equipment numbering or non-standard terminology); Understandably, highlighting different colored labels (green, yellow, red) on the front-end interface can intuitively distinguish correct, missing, and incorrect safety measures in the work order, thereby significantly improving the efficiency of maintenance personnel in identifying the status of safety measures and reducing the time and error rate of manual inspection.

[0099] Optionally, after obtaining the work order completion information, in addition to highlighting the work order completion information on the front-end interface, a topology diagram can be attached next to the work order completion information. This simultaneously displays the associated network topology of the equipment being maintained, thereby assisting maintenance personnel in understanding the logic of the security measures. In the implementation of the above solution, attaching a topology diagram next to the work order completion information allows for the simultaneous display of the associated network topology of the equipment being maintained, enabling maintenance personnel to more intuitively understand the logical relationships of the security measures, thus improving the accuracy of understanding and implementing security measures in complex network environments. Furthermore, by combining color-coding and the topology diagram display method, not only is visual feedback provided, but the overall grasp of security measures by maintenance personnel is also enhanced, thereby reducing operational risks caused by incomplete information understanding and improving the reliability and security of work order execution.

[0100] Please see Figure 5 The diagram shown is a structural schematic of an intelligent verification device for electrical work permit safety measures based on a safety measures knowledge base, provided in an embodiment of this application. This embodiment of the application provides an intelligent verification device 200 for electrical work permit safety measures based on a safety measures knowledge base, comprising: The number type parsing module 210 is used to parse the target equipment number and target operation type of the target equipment from the work order content of the target power plant during the operation process.

[0101] The query statement lookup module 220 is used to obtain the target device type corresponding to the target device number, and to search for the corresponding device lookup path rule query statement and device safety measure terminology template from the safety measure knowledge base based on the target device type and target operation type. The safety measure knowledge base stores the correspondence between device lookup path rule query statements, device safety measure terminology templates, device types and operation types.

[0102] The associated device query module 230 is used to query the associated device numbers that have an electrical topology connection with the target device from the power grid diagram database by using the target device number as the input parameter of the device search path rule query statement.

[0103] The safety measure content generation module 240 is used to generate safety measure content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type.

[0104] The content intelligent verification module 250 is used to intelligently verify the work order content based on the safety measures content to obtain standard electrical work order content.

[0105] As an optional implementation of the above-mentioned device, the query statement lookup module includes: The Equipment Type Lookup Submodule is used to find the target equipment type corresponding to the target equipment number from the equipment ledger table. The equipment ledger table stores the correspondence between equipment identifiers and equipment types.

[0106] As an optional implementation of the above-mentioned device, the associated device number includes a primary device number and a secondary device number; the security content generation module includes: The secondary equipment query submodule is used to query the primary equipment number and secondary equipment number from the power grid diagram database based on the target equipment number.

[0107] The equipment information acquisition submodule is used to retrieve equipment information corresponding to primary equipment numbers and secondary equipment numbers from the equipment ledger table.

[0108] The safety measure template filling submodule is used to fill the equipment safety measure terminology template with the equipment information corresponding to the primary equipment number, the equipment information corresponding to the secondary equipment number, the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, and the target operation type to obtain the safety measure content.

[0109] As an optional implementation of the above-mentioned device, the security content generation module includes: The equipment information acquisition submodule is used to obtain the target equipment information corresponding to the target equipment number and the associated equipment information corresponding to the associated equipment number from the equipment ledger table.

[0110] The topology relationship retrieval submodule is used to retrieve topology relationship information between target devices and associated devices using the knowledge graph of the power grid graph database.

[0111] The template variable replacement submodule is used to generate safety measure prompt engineering text based on target device information, associated device information, target operation type, device safety measure terminology template, and topology relationship device information.

[0112] The prompt text input submodule is used to input the prompt engineering text of the safety measures into the pre-trained language model, so that the pre-trained language model can generate the safety measure content based on the target device information, associated device information, device safety measure terminology templates and target operation type. The safety measure content conforms to the target device type and target operation type.

[0113] As an optional implementation of the above-mentioned device, the content intelligent verification module includes: The comparison result acquisition submodule is used to compare the content of the safety measures with the content of the work order and obtain the comparison result.

[0114] The Engineering Text Acquisition Submodule is used to obtain a preset intelligent verification prompt word template, and replace the template variables in the intelligent verification prompt word template with the comparison results, safety measures content, and work order content to obtain the intelligent verification prompt engineering text.

[0115] The verification content acquisition submodule is used to input the intelligent verification prompt engineering text into the pre-trained language model, so that the pre-trained language model can intelligently verify the work order content in the prompt engineering text based on the safety measures content and comparison results, and obtain the standard electrical work order content.

[0116] As an optional implementation of the above-mentioned device, the intelligent verification device for electrical work permit safety measures based on the safety measures knowledge base further includes: The work permit information completion module is used to determine the work permit completion information for the target equipment during the operation process based on the content of the standard electrical work permit.

[0117] As an optional implementation of the above-mentioned device, the work order information improvement module includes: The first information addition submodule is used to add the comparison result of the discrepancy between the equipment number of the target equipment in the work order content and the equipment number in the standard electrical work order content to the work order improvement information if the equipment number of the target equipment is inconsistent.

[0118] The second information addition submodule is used to add the comparison result of the mismatch between the measure terms of the target equipment in the work order content and the measure terms in the standard electrical work order content to the work order improvement information if the measure terms of the target equipment do not match.

[0119] The third information addition submodule is used to add the associated devices from the standard electrical work order to the work order completion information if the number of associated devices of the target device in the work order content is less than the number of associated devices in the standard electrical work order content.

[0120] The fourth information addition submodule is used to add the operation order from the standard electrical work order to the work order completion information if the operation order in the work order content does not match the operation order in the standard electrical work order content.

[0121] It should be understood that this device corresponds to the above-described embodiment of the intelligent verification method for electrical work permit safety measures based on a safety knowledge base, and is capable of performing the various steps involved in the above-described method embodiment. The specific functions of this device can be found in the description above, and detailed descriptions are appropriately omitted here. The device includes at least one software functional module that can be stored in memory or embedded in the device's operating system (OS) in the form of software or firmware.

[0122] Please see Figure 6 The diagram shows a structural schematic of an electronic device provided in an embodiment of this application. An electronic device 300 provided in this application includes a processor 310 and a memory 320. The memory 320 stores machine-readable instructions executable by the processor 310. When the machine-readable instructions are executed by the processor 310, the method described above is performed.

[0123] This application embodiment also provides a computer-readable storage medium 330, on which a computer program is stored. This computer program is executed by a processor 310 to perform the methods described above. The computer-readable storage medium 330 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0124] This application also provides a computer program product, including: a computer program or computer instructions, which are executed by a processor to perform the method described above.

[0125] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0126] It should be understood that the disclosed apparatus and methods can also be implemented in other ways, as provided in the embodiments of this application. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending primarily on the functions involved.

[0127] Furthermore, the functional modules of each embodiment in this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part. In addition, in the description of this specification, the reference to terms such as "one embodiment," "some embodiments," "example," "specific example," "some examples," etc., means that the specific feature, structure, material, or characteristic described in connection with that embodiment or example is 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. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0128] The above description is only an optional implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be covered within the protection scope of the embodiments of this application.

Claims

1. A method for intelligent verification of electrical work permit safety measures based on a safety measure knowledge base, characterized in that, include: Extract the target equipment number and target operation type from the work order content during the operation of the target power plant; Obtain the target device type corresponding to the target device number, and search for the device search path rule query statement and device safety measure terminology template corresponding to the target device from the safety measure knowledge base according to the target device type and the target operation type. The safety measure knowledge base stores the correspondence between device search path rule query statements, device safety measure terminology templates, device types and operation types. Using the target device number as the input parameter of the device lookup path rule query statement, the system queries the power grid diagram database for associated device numbers that have an electrical topology connection with the target device. Based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type, generate safety measure content; The work order content is intelligently verified based on the safety measures described above to obtain standard electrical work order content.

2. The method according to claim 1, characterized in that, The step of obtaining the target device type corresponding to the target device number includes: The target equipment type corresponding to the target equipment number is found in the equipment ledger table, which stores the correspondence between equipment identifiers and equipment types.

3. The method according to claim 2, characterized in that, The associated device number includes a primary device number and a secondary device number; the step of generating safety measure content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type includes: Based on the target device number, query the primary device number and the secondary device number from the power grid diagram database; Obtain the equipment information corresponding to the primary equipment number and the equipment information corresponding to the secondary equipment number from the equipment ledger table; Fill the equipment information corresponding to the primary equipment number, the equipment information corresponding to the secondary equipment number, the target equipment information corresponding to the target equipment number, the associated equipment information corresponding to the associated equipment number, and the target operation type into the equipment safety measure terminology template to obtain the safety measure content.

4. The method according to claim 2, characterized in that, The step of generating security measures content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device security terminology template, and the target operation type includes: Obtain the target device information corresponding to the target device number and the associated device information corresponding to the associated device number from the equipment ledger table; The topological relationship between the target device and the associated devices is retrieved using the knowledge graph of the power grid database. Based on the target device information, the associated device information, the target operation type, the device safety measure terminology template, and the topology relationship device information, generate a prompt engineering text for safety measures; The engineering text prompting the safety measures is input into a pre-trained language model, so that the pre-trained language model generates the safety measures content based on the target device information, the associated device information, the device safety measure terminology template, and the target operation type. The safety measures content conforms to the target device type and the target operation type.

5. The method according to claim 4, characterized in that, The intelligent verification of the work order content based on the security measures includes: The safety measures are compared with the work order to obtain the comparison results; Obtain a preset intelligent verification prompt word template, and replace the template variable in the intelligent verification prompt word template with the comparison result, the content of the safety measures, and the content of the work order to obtain the intelligent verification prompt engineering text; The intelligent verification prompt engineering text is input into the pre-trained language model, so that the pre-trained language model can intelligently verify the work order content in the prompt engineering text according to the safety measures content and the comparison results, and obtain the standard electrical work order content.

6. The method according to any one of claims 1-5, characterized in that, After obtaining the contents of the standard electrical work order, the following is also included: The work permit completion information for the target equipment during operation is determined based on the content of the standard electrical work permit.

7. The method according to claim 5, characterized in that, The step of determining the work permit completion information for the target equipment during operation based on the content of the standard electrical work permit includes: If the device number of the target device in the work order content is inconsistent with the device number in the standard electrical work order content, the comparison result of the inconsistency of the device number of the target device is added to the work order completion information; If the terminology for the measures of the target equipment in the work order does not match the terminology for the measures in the standard electrical work order, the comparison result of the mismatch between the terminology for the target equipment and the work order completion information shall be added to the work order completion information. If the number of associated devices of the target device in the work order content is less than the number of associated devices in the standard electrical work order content, then the associated devices in the standard electrical work order content are added to the work order completion information; If the operation sequence in the work order does not match the operation sequence in the standard electrical work order, then the operation sequence in the standard electrical work order will be added to the work order completion information.

8. An intelligent verification device for electrical work permit safety measures based on a safety measures knowledge base, characterized in that, include: The number type parsing module is used to parse the target equipment number and target operation type from the work order content of the target power plant during the operation process; The query statement lookup module is used to obtain the target device type corresponding to the target device number, and search for the device lookup path rule query statement and device safety measure terminology template corresponding to the target device from the safety measure knowledge base according to the target device type and the target operation type. The safety measure knowledge base stores the correspondence between device lookup path rule query statements, device safety measure terminology templates, device types and operation types. The associated device query module is used to use the target device number as the input parameter of the device search path rule query statement to query the associated device numbers that have an electrical topology connection relationship with the target device from the power grid diagram database; The safety measure content generation module is used to generate safety measure content based on the target device information corresponding to the target device number, the associated device information corresponding to the associated device number, the device safety measure terminology template, and the target operation type. The content intelligent verification module is used to intelligently verify the work order content based on the safety measures content to obtain standard electrical work order content.

9. An electronic device, characterized in that, include: A processor and a memory, the memory storing machine-readable instructions executable by the processor, the machine-readable instructions being executed by the processor to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the method according to any one of claims 1 to 7.

11. A computer program product, characterized in that, include: A computer program or computer instructions that, when executed by a processor, perform the method according to any one of claims 1 to 7.

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