Method and system for parameter configuration and closed-loop verification of electric energy meter based on multi-agent cooperation

Abstract

The method and system for parameter configuration and closed-loop verification of electric energy meter based on multi-agent cooperation belong to the technical field of smart grid manufacturing and industrial internet of things.The method comprises the following steps: step 102, receiving a customer technical specification document, performing semantic analysis on the document, extracting explicit parameter requirements and implicit default rule mapping in the document to generate a parameter template file; step 104, comparing and verifying the parameter template file with the customer technical specification document; step 106, uploading the verified parameter template file to a controlled file server and generating a unique identifier; based on the unique identifier, matching and loading the corresponding parameter template file from the controlled file server to the local; step 108, reading the actual effective parameters in the electric energy meter, comparing with the locally loaded parameter template file, and outputting the verification result. The present application ensures that the parameters of the electric energy meter connected to the power grid meet the original demands of the customer and the industry standards by constructing a complete closed-loop trust chain.

Description

Technical Field

[0001] This invention relates to the fields of smart grid manufacturing and industrial Internet of Things (IIoT) technology, and in particular to a method and system for automatically parsing, securely distributing, and verifying the factory parameters of electricity meters by combining Large Language Model (LLM) and Multi-Agent collaborative technology. Background Technology

[0002] In the mass production and delivery of electricity meters, the configuration of factory parameters is a core element determining whether the product can meet customer customization needs. The existing parameter configuration and production parameter design processes have the following significant pain points:

[0003] 1. Manual parsing is inefficient and prone to errors: Process engineers need to manually read lengthy, unstructured technical specification documents provided by clients, extract parameter requirements, and manually fill in parameter templates. Faced with complex implicit rules and default value clauses, human errors such as "misreading" and "omissions" are very likely to occur.

[0004] 2. Cross-process verification is time-consuming and lacks traceability: Test engineers need to manually compare the parameter templates configured by process engineers with customer specifications a second time, which not only consumes a lot of time, but also makes it difficult to guarantee the accuracy rate.

[0005] 3. Serious security risks exist in file transfer: The parameter template file is downloaded independently by production line personnel from the PLM system and manually imported into the host computer of the production software. This makes it very easy for fatal error prevention failures such as "using the wrong file version" and "misattributing files" to occur.

[0006] 4. Manual closed-loop verification at the production line terminal is inefficient and prone to errors: In the traditional mode, the parameters in the table are manually verified by the production line QC personnel, which is inefficient and prone to human errors such as "misreading" or "missing". Summary of the Invention

[0007] The purpose of this invention is to solve the problems existing in the prior art and provide a method and system for configuring and verifying electricity meter parameters based on multi-agent collaboration. By constructing a complete closed-loop trust chain, it ensures that the parameters of the electricity meter connected to the power grid meet the original requirements of customers and industry standards.

[0008] The objective of this invention is achieved through the following technical solution:

[0009] The method for configuring and verifying electricity meter parameters based on multi-agent collaboration includes the following steps:

[0010] Step 102: Receive the customer's technical specification document, perform semantic parsing on the document, extract the explicit parameter requirements and implicit default rules in the document, and map them to generate a parameter template file that conforms to the preset format;

[0011] Step 104: Compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated.

[0012] Step 106: Upload the verified parameter template file to the controlled file server and generate a unique identifier; based on the unique identifier, match and load the corresponding parameter template file from the controlled file server to the local machine;

[0013] Step 108: Read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

[0014] Preferably, step 102 includes: identifying the correlation between parameters so that when a parameter is modified, other parameters associated with it are updated.

[0015] Preferably, step 104 includes: if there is an anomaly in the comparison result, generating an anomaly warning list of the causes of the anomaly, and verifying it after receiving a manual confirmation instruction.

[0016] Preferably, step 106 includes: performing integrity verification and order consistency verification on the parameter template file, and loading it locally after the verification is passed.

[0017] Preferably, step 108 includes: after verification, binding the unique identifier, parameter template file version number, electricity meter asset number and verification time to generate production traceability data.

[0018] This manual also provides a multi-agent collaborative system for configuring and verifying electricity meter parameters, including:

[0019] The parsing module is used to receive customer technical specification documents, perform semantic parsing on the documents, extract explicit parameter requirements and implicit default rules from the documents, and map them to generate parameter template files that conform to a preset format.

[0020] The audit module is used to compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated.

[0021] The distribution module is used to upload the verified parameter template file to the controlled file server and generate a unique identifier; based on the unique identifier, it matches and loads the corresponding parameter template file from the controlled file server to the local machine;

[0022] The verification module is used to read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

[0023] Preferably, the parsing module, auditing module, and verification module are all deployed on cloud servers or local edge computing nodes, and communicate asynchronously and synchronize status through message queues.

[0024] This specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the methods described above.

[0025] This specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods described above.

[0026] The advantages of this invention are: by constructing an intelligent trust chain of "semantic parsing → logical auditing → secure distribution → closed-loop verification", it achieves a qualitative change in the configuration of electricity meter parameters from "manual dependence" to "zero-error self-verification", thereby eliminating ambiguity and deviation in the generation, transmission and execution of parameter templates, and ensuring that the parameters of the electricity meter connected to the power grid meet the original requirements of customers and industry standards. Attached Figure Description

[0027] Figure 1 A flowchart of a method for configuring and verifying electricity meter parameters based on multi-agent collaboration, provided in the embodiments of this specification;

[0028] Figure 2 A block diagram of a multi-agent collaborative energy meter parameter configuration and closed-loop verification system provided in the embodiments of this specification;

[0029] Figure 3 This is a block diagram of the internal structure of a computer device provided in the embodiments of this specification. Detailed Implementation

[0030] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0031] like Figure 1 As shown, this embodiment provides a method for configuring and verifying electricity meter parameters based on multi-agent collaboration, including the following steps:

[0032] Step 102: Receive the customer's technical specification document, perform semantic parsing on the document, extract the explicit parameter requirements and implicit default rules in the document, and map them to generate a parameter template file that conforms to the preset format.

[0033] Specifically, customer technical specifications are generally unstructured documents, therefore requiring semantic parsing using a Large Language Model (LLM) to accurately extract explicit parameter requirements and implicit default rules. Explicit parameter requirements refer to those explicitly written into the document by the customer. For example, if the document states: "This order applies to three-phase four-wire energy meters, rated voltage 220V, basic current 5A, maximum current 60A, communication interface RS485, protocol conforming to DL / T 645-2007," then the extracted explicit parameter requirements are as follows:

[0034] Wiring method Three-phase four-wire Rated voltage 220V Basic Current 5A Maximum current 60A Communication interface RS485 Communication Protocol DL / T 645-2007

[0035] Implicit default rules are constraints that, while not explicitly stated in the documentation, must be followed according to industry standards. For example, if the documentation only states "rated voltage 220V," and according to the DL / T 698 standard, the voltage operating range is 80% to 115% of the rated voltage, then the extracted implicit default rule is "rated voltage lower limit 176V, upper limit 253V." Similarly, if the documentation only states "three-phase four-wire," then the phase angle between the three phase voltages defaults to 120°, and the extracted implicit default rule is "phase angle 120°."

[0036] After extracting all explicit parameter requirements and implicit default rules, they are automatically mapped to standard parameter templates, such as the table above. These templates have a preset format, and you only need to fill in the parameters in the corresponding positions to generate a parameter template file that conforms to the preset format.

[0037] In addition, when extracting parameters, the system automatically identifies the relationships between parameters so that when a parameter is modified, other related parameters are updated to ensure global consistency of the configuration. For example, if the wiring method mentioned above is three-phase four-wire, and the associated parameter is a phase angle of 120°, if the wiring method is changed to three-phase three-wire, the phase angle will automatically update to 60°.

[0038] We can also add a parsing channel for key parameters, such as a "hard parsing" channel based on regular expressions / rule engines. This means that key parameters are parsed using dual channels. For key parameters such as voltage threshold and accuracy level, in addition to semantic parsing through a large language model, "hard parsing" is performed simultaneously. If the two results are consistent, the parameter passes; if they are inconsistent, step 104 will audit and adjudicate the conflict between the two to ensure the accuracy of the parameters.

[0039] Step 104: Compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated.

[0040] Specifically, this step not only verifies the accuracy of parameter values ​​(i.e., explicit parameter requirements) but also checks whether the default values ​​comply with the catch-all clauses of the specification (i.e., implicit default rules). If the verification passes, a traceability verification report with document anchors (page numbers, paragraphs) is generated and the process is approved. If anomalies are found in the comparison results, such as logical conflicts in parameter configurations or non-compliance with specification clauses, an anomaly warning list containing specific reasons for the conflicts and references to the original specification text is generated. After receiving manual confirmation instructions, the process passes verification, a traceability verification report is generated, and the process is approved.

[0041] Additionally, this step can also verify "contextual attribution." For example, a customer document might mention multiple electricity meter models, and a certain parameter might be "for model A." If it's mapped to "model B," it could lead to an error. Of course, the parameter might also apply to "model B," and the parameter for "model A" might have a default setting, meaning it wouldn't cause an error. Therefore, we can configure it as follows: if the "contextual attribution" matches exactly, proceed; if the default value matches as a fallback, manual confirmation is required; if there's a conflict, the verification fails.

[0042] Step 106: Upload the verified parameter template file to the controlled file server and generate a unique identifier; based on the unique identifier, match and load the corresponding parameter template file from the controlled file server to the local machine.

[0043] Specifically, the unique identifier can be the order number, which is then used to name the document. At the production station, production staff only need to scan the order number in the production software. The host computer system automatically sends a request to the server, accurately matches and loads the corresponding parameter template to the local machine, without requiring manual intervention in the file path. Furthermore, before loading the parameter template file, the system automatically performs integrity checks and order consistency checks on the parameter template file; only after the checks pass are the parameters loaded locally.

[0044] In addition, to prevent parameter template files from being tampered with, hash values ​​can be generated and stored on the controlled file server. The hash values ​​are compared before loading the parameter template file locally, and if they match, the file is loaded.

[0045] Step 108: Read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

[0046] After the host computer sets the parameters from the parameter template file to the energy meter, it reads the actual effective parameters inside the energy meter through the communication interface and compares and verifies them with the locally loaded parameter template. If an inconsistency is found, the system automatically intercepts and issues an alarm; after the comparison is successful, the final verification result is output, and the unique identifier, parameter template file version number, energy meter asset number, and verification time are bound together to generate production traceability data.

[0047] As described above, this embodiment provides a complete intelligent trust chain of "semantic parsing → logical auditing → secure distribution → closed-loop verification." This chain not only achieves a closed loop overall, ensuring that the parameters of the final electricity meter connected to the grid meet the customer's original requirements and industry standards, but also includes corresponding verification mechanisms between each two steps. This prevents problems from accumulating and escalating, narrows the scope of the issues, and allows for timely detection and correction of errors, ensuring overall work efficiency.

[0048] like Figure 2 As shown, this manual also provides a multi-agent collaborative system for configuring and verifying electricity meter parameters, including:

[0049] The parsing module is used to receive customer technical specification documents, perform semantic parsing on the documents, extract explicit parameter requirements and implicit default rules from the documents, and map them to generate parameter template files that conform to a preset format.

[0050] The audit module is used to compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated.

[0051] The distribution module is used to upload the verified parameter template file to the controlled file server and generate a unique identifier; based on the unique identifier, it matches and loads the corresponding parameter template file from the controlled file server to the local machine;

[0052] The verification module is used to read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

[0053] The parsing module, auditing module, and verification module are all deployed on cloud servers or local edge computing nodes. They communicate asynchronously and synchronize status through message queues to improve the system's concurrent throughput, network disconnection tolerance, and production line expansion flexibility.

[0054] like Figure 3 As shown, this specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the methods described above. In the figure, Agent1-Agent3 represent the parsing module, auditing module, and verification module described above, respectively. The collaborative decision-making center is used to coordinate multiple modules to implement the methods described above.

[0055] This specification also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods described above.

[0056] The above are merely preferred embodiments of the present invention, and are implementations based on the overall concept of the present invention. Furthermore, the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for configuring and verifying electricity meter parameters based on multi-agent collaboration, characterized in that, Includes the following steps: Step 102: Receive the customer's technical specification document, perform semantic parsing on the document, extract the explicit parameter requirements and implicit default rules in the document, and map them to generate a parameter template file that conforms to the preset format; Step 104: Compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated. Step 106: Upload the verified parameter template file to the controlled file server and generate a unique identifier; Based on a unique identifier, the corresponding parameter template file is matched from the controlled file server and loaded to the local machine; Step 108: Read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

2. The method for configuring and verifying electricity meter parameters based on multi-agent collaboration according to claim 1, characterized in that, Step 102 includes: identifying the correlation between parameters so that when a parameter is modified, other parameters associated with it are updated.

3. The method for configuring and verifying electricity meter parameters based on multi-agent collaboration according to claim 1, characterized in that, Step 104 includes: if there is an anomaly in the comparison result, generating an anomaly warning list of the causes of the anomaly, and verifying it after receiving a manual confirmation instruction.

4. The method for configuring and verifying electricity meter parameters based on multi-agent collaboration according to claim 1, characterized in that, Step 106 includes: performing integrity verification and order consistency verification on the parameter template file, and loading it locally after the verification is passed.

5. The method for configuring and verifying electricity meter parameters based on multi-agent collaboration according to claim 1, characterized in that, Step 108 includes: after verification, binding the unique identifier, parameter template file version number, electricity meter asset number and verification time to generate production traceability data.

6. A multi-agent collaborative energy meter parameter configuration and closed-loop verification system, characterized in that, include: The parsing module is used to receive customer technical specification documents, perform semantic parsing on the documents, extract explicit parameter requirements and implicit default rules from the documents, and map them to generate parameter template files that conform to a preset format. The audit module is used to compare the parameter template file with the customer's technical specification document to verify whether the explicit parameter requirements and implicit default rules in the parameter template file are accurate. After the verification is passed, a traceability verification report is generated. The distribution module is used to upload the verified parameter template file to the controlled file server and generate a unique identifier; Based on a unique identifier, the corresponding parameter template file is matched from the controlled file server and loaded to the local machine; The verification module is used to read the actual effective parameters in the electricity meter, compare them with the parameter template file loaded locally, and output the verification result.

7. The energy meter parameter configuration and closed-loop verification system based on multi-agent collaboration according to claim 6, characterized in that, The parsing module, auditing module, and verification module are all deployed on cloud servers or local edge computing nodes, and communicate asynchronously and synchronize their states through message queues.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

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