A Dynamic Update System for Electrical Design Knowledge Base Based on a Large Language Model

Abstract

This invention discloses a dynamic update system for an electrical design knowledge base based on a large language model, comprising a cross-modal mutual-driven update module, a design error feedback closed-loop module, a specification real-time synchronization module, a multi-expert collaborative certification module, a knowledge storage module, a CAD interface interaction module, and a large language model processing module. Through three core innovations—cross-modal mutual-driven updates, fully automated updates, and multi-layered precise verification—this invention thoroughly solves the shortcomings of existing solutions, such as passive updates, low accuracy, lagging compliance, and high costs. It achieves a triple effect: significantly improved knowledge update efficiency, improved design compliance pass rates, and effective reduction in overall costs. Furthermore, by reconstructing the knowledge management logic of electrical design through a two-way closed loop, it provides an intelligent solution for electrical design scenarios with high professionalism and high compliance requirements.

Description

Technical Field

[0001] This invention relates to the field of electrical design knowledge base system technology, and in particular to a dynamic update system for electrical design knowledge base based on a large language model. Background Technology

[0002] The core function of the electrical design knowledge base system is to serve as a tool for storing and retrieving basic knowledge in the field of electrical design. It provides standardized and reusable knowledge resources for the entire design process, reduces the cost of acquiring basic information, and ensures basic compliance and efficiency in design work.

[0003] Traditional knowledge repositories suffer from pain points such as delayed updates, high maintenance costs, low retrieval efficiency, and difficulty in knowledge reuse, failing to meet the electrical design field's demands for timely, accurate, and intelligent knowledge.

[0004] Therefore, those skilled in the art provide a dynamic updating system for an electrical design knowledge base based on a large language model to solve the problems mentioned in the background art. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a dynamic update system for an electrical design knowledge base based on a large language model, comprising a cross-modal mutual-driven update module, a design error feedback closed-loop module, a specification real-time synchronization module, a multi-expert collaborative authentication module, a knowledge storage module, a CAD interface interaction module, and a large language model processing module; The cross-modal mutual-driven update module is used to realize cross-modal acquisition, alignment and bidirectional mutual-driven update of CAD drawing vector data, text knowledge data and electrical specification data; The design error feedback closed-loop module is used to collect verification error data in the electrical design process, locate knowledge gaps in the knowledge base, generate update tasks, and optimize the knowledge base and design verification rules in a closed loop after expert verification. The aforementioned real-time synchronization engine is used to connect to the official electrical specification data source to achieve clause-level difference comparison, accurate replacement, version tracking, and design scenario adaptation push. The multi-expert collaborative certification module performs LLM pre-verification according to professional sub-review permissions, supports online annotation by multiple people, and automatically summarizes the points of disagreement and generates compromise suggestions. The knowledge storage module adopts a hybrid storage architecture of electrical design-specific knowledge graph + vector library + version library; The CAD interface interaction module is used to establish communication with at least one of AutoCAD Electrical, power design software, and EPLANElectric P8 to realize data acquisition, knowledge push, error feedback, and change synchronization. The large language model processing module adopts a finely tuned large language model from the electrical domain for standardized text splitting, knowledge triple extraction, error root cause analysis, difference change judgment, and expert opinion fusion.

[0006] Preferably, the cross-modal mutual-driven update module constructs an electrical design cross-modal knowledge graph schema, and uses knowledge graph node similarity and vector retrieval to achieve incremental updates of cross-modal data, avoiding duplication. Specifically: A. Newly added components in drawings will be automatically added to the knowledge graph component library and associated with the corresponding selection specifications; B. Newly added clauses in the text will provide feedback on the drawing verification rules and mark design nodes that do not conform to the new specifications; thus solving the pain point of the lack of synchronization between drawings and textual knowledge.

[0007] Preferably, the specific functions of the cross-modal mutual-drive update module include: A. Cross-modal data acquisition: Through the interface protocol with CAD design software, multi-source data in the entire electrical design process is collected synchronously. The multi-source data includes vectorized data of CAD drawings, component selection text data, electrical specification clause data, and engineering change data. B. Cross-modal data processing: The YOLO object detection algorithm is used to extract component entities, wiring relationships and layout rules from the drawings. The specification text and selection manual are split by a large language model fine-tuned in the electrical field to extract knowledge triples. The CLIP model is used to achieve cross-modal alignment between the vectorized drawing results and the text knowledge nodes. C. Mutual-driven update trigger: When new cross-modal data is collected, if the drawing data adds new components / wiring relationships, the corresponding nodes and relationships in the knowledge graph of the knowledge base will be automatically updated; if the text knowledge is updated, the intelligent annotation and verification rules of the drawing will be optimized through the CAD interface. D. Incremental Update Verification: Based on the node incremental learning algorithm of graph neural network, only the nodes that have changed in the knowledge base are updated. The accuracy of the update is confirmed by a multi-professional expert collaborative verification module, and a version record with a timestamp is generated.

[0008] Preferred method for constructing a cross-modal knowledge graph schema for electrical design includes the following steps: S1. Define the cross-modal core entity set: construct specification entities, component entities, design scenario entities, selection / wiring rule entities, design error entities, knowledge gap entities, and version entities. Each of these entities contains cross-modal mapping fields. S2. Entity Attribute Constraints: Configure electrical design-specific core attributes for each entity. Among them, the specification entity includes the standard number, clause content, and cross-modal mapping ID; the component entity includes the model, parameters, and drawing mapping ID; and the design error entity includes the error type, associated component / circuit ID, and corresponding drawing ID. S3. Cross-modal relationship definition: Establish three exclusive relationships: cross-modal alignment drawing, knowledge mapping specification, and scenario adaptation. The cross-modal alignment relationship associates the vectorized entities of the drawing with the text knowledge nodes through the mapping ID generated by the CLIP model, realizing a unique mapping between component model - terminal number - wiring path and component entity - wiring rule - specification basis; S4.Schema Integrity Verification: Verify whether entity attributes and relationship definitions cover the knowledge association requirements of the entire electrical design process through electrical-specific LLM, ensuring 95% accuracy of association when cross-modal data is mutually driven.

[0009] Preferably, the design error feedback closed-loop module constructs an error collection-root cause analysis-knowledge correction-verification and implementation closed loop, specifically: A. The software outputs a validation error; B.LLM analyzes the root causes of errors: locating errors in the knowledge base, and identifying vague / outdated descriptions; C. Generate an update task and push it to experts for review; D. After the review is approved, the knowledge base will be automatically updated, and feedback will be provided to the design software to optimize the verification rules.

[0010] Preferably, the real-time specification synchronization module has a built-in specification dynamic monitoring and precise replacement module: - It connects to official databases such as GB / T, IEC, and DL / T to capture standard updates in real time. The LLM automatically splits the updated clauses, matches them with the corresponding old clauses in the knowledge base, and generates replacement suggestions. + The version traceability chain supports filtering specifications according to design scenarios to avoid redundant updates.

[0011] Preferably, the CAD interface protocol specification of the CAD interface interaction module is used to realize bidirectional interaction between the CAD design software and the knowledge base dynamic update system, specifically including the following: A. Interface Function Set Definition: Includes data acquisition interface, knowledge push interface, verification feedback interface, and engineering change synchronization interface. These interfaces correspond to the entire process of electrical design selection, drawing, verification, and change, respectively. B. Data transmission specifications: Structured data uses JSON format, vectorized drawing data uses XML format, binary files use Base64 encoding, local communication uses the Socket protocol, and cross-device communication uses the HTTPS protocol; C. Security Mechanism: It adopts triple protection of device authentication + user token + AES-256 data encryption. Device authentication is verified by hardware SN number, user token is valid for 24 hours, and data transmission encryption key is rotated periodically; D. Error handling mechanism: When the interface call fails, the CAD software caches the data and starts automatic retry. The retry interval is 3 seconds. After 3 failed retries, a manual synchronization prompt is triggered to ensure that no data is lost.

[0012] Preferably, the standard real-time synchronization engine includes the following core modules: A. Multi-source standard access module: Connects to official data sources such as the National Standardization Management Committee, China Electricity Council, and International Electrotechnical Commission, and obtains updated data of GB / T, DL / T, and IEC series electrical standards in real time through API calls, data subscriptions, or compliant crawling. B. Clause-level Difference Comparison Module: Employs a cosine similarity algorithm combined with electrical domain keyword weighting to compare the clause content of the new and old specifications. It uses an electrical-specific LLM to determine whether the changes are substantial and marks newly added / modified / repeated clauses. C. Precise Replacement and Version Tracking Module: Precisely replaces modified clauses, retaining the old version content and the reason for replacement; marks obsolete clauses with status and retains the original text; associates new clauses with corresponding design scenario tags, generating a traceability chain containing specification number - version - change content - affected project; D. Design Scenario Adaptation Push Module: Filter updated specifications according to the scenario type of electrical design projects, and push specification update notifications and adaptation suggestions to design projects that are using the specification through the CAD interface, prompting designers to check.

[0013] The technical effects and advantages of this invention are as follows: Compared with the prior art, the beneficial effects of the present invention are: This invention, through its three core innovations—cross-modal mutual drive, full-process automatic updating, and multi-layer precise verification—completely solves the shortcomings of existing solutions, such as passive updates, low accuracy, lagging compliance, and high costs. It achieves a triple effect of greatly improving knowledge update efficiency and design compliance pass rate, and effectively reducing overall costs. At the same time, it reconstructs the knowledge management logic of electrical design through a two-way closed loop, providing an intelligent solution for electrical design scenarios with high professionalism and high compliance requirements. Attached Figure Description

[0014] Figure 1 This is a structural block diagram of the dynamic update system for electrical design knowledge base based on a large language model provided in the embodiments of this application. Detailed Implementation

[0015] The present invention will now be described in further detail with reference to specific embodiments. The embodiments of the present invention are given for illustrative and descriptive purposes only, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described to better illustrate the principles and practical application of the invention, and to enable those skilled in the art to understand the invention and design various embodiments with various modifications suitable for a particular purpose.

[0016] Example 1 Please see Figure 1 This embodiment provides a dynamic update system for an electrical design knowledge base based on a large language model, characterized by including a cross-modal mutual-driven update module, a design error feedback closed-loop module, a specification real-time synchronization module, a multi-expert collaborative certification module, a knowledge storage module, a CAD interface interaction module, and a large language model processing module; The cross-modal mutual-driven update module is used to realize cross-modal acquisition, alignment and bidirectional mutual-driven update of CAD drawing vector data, text knowledge data and electrical specification data; The design error feedback closed-loop module is used to collect verification error data in the electrical design process, locate knowledge gaps in the knowledge base, generate update tasks, and optimize the knowledge base and design verification rules in a closed loop after expert verification. The real-time synchronization module of the specifications is used to connect to the official electrical specification data source to realize clause-level difference comparison, accurate replacement, version tracking and design scenario adaptation push. The multi-expert collaborative certification module further subdivides review permissions according to professional fields (such as high-voltage equipment / low-voltage circuits / control logic). LLM pre-verification: detects conflicts between updated content and existing knowledge, compliance with standards, and accuracy of expression. Opinion fusion: supports online annotation by multiple users. LLM automatically summarizes disagreements and generates compromise suggestions, generates the final updated version, and records review traces. This solves the problem of unreliable accuracy in updating existing solutions and adapts to the highly professional requirements of electrical design.

[0017] The knowledge storage module adopts a hybrid storage architecture of electrical design-specific knowledge graph + vector library + version library. The knowledge graph includes specification entities, component entities, design scenario entities, selection / wiring rule entities, design error entities, knowledge gap entities, and version entities. Moreover, each entity is linked through cross-modal mapping relationships, rule association relationships, and version traceability relationships. The CAD interface interaction module is used to establish communication with at least one of AutoCAD Electrical, GstarCAD Power Design Software, and EPLANElectric P8 to realize data acquisition, knowledge push, error feedback, and change synchronization. The large language model processing module adopts a finely tuned large language model from the electrical domain for standardized text splitting, knowledge triple extraction, error root cause analysis, difference change judgment, and expert opinion fusion.

[0018] The cross-modal mutual-driven update module constructs an electrical design cross-modal knowledge graph schema. Based on knowledge graph node similarity and vector retrieval, it achieves incremental updates of cross-modal data, avoiding duplication. Specifically: A. Newly added components in drawings will be automatically added to the knowledge graph component library and associated with the corresponding selection specifications; B. Newly added clauses in the text will provide feedback on the drawing verification rules and mark design nodes that do not conform to the new specifications; thus solving the pain point of the lack of synchronization between drawings and textual knowledge.

[0019] The specific functions of the cross-modal mutual drive update module include: A. Cross-modal data acquisition: Through the interface protocol with CAD design software, multi-source data in the entire electrical design process is collected synchronously. The multi-source data includes vectorized data of CAD drawings, component selection text data, electrical specification clause data, and engineering change data. B. Cross-modal data processing: The YOLO object detection algorithm is used to extract component entities, wiring relationships and layout rules from the drawings. The specification text and selection manual are split by the large language model (LLM) fine-tuned in the electrical domain to extract knowledge triples. The CLIP model is used to achieve cross-modal alignment between the vectorized drawing results and the text knowledge nodes. C. Inter-driven update trigger: When new cross-modal data is collected, if the drawing data adds new components / wiring relationships, the corresponding nodes and relationships in the knowledge graph of the knowledge base will be automatically updated; if the text knowledge (specification / manual) is updated, the intelligent annotation and verification rules of the drawing will be optimized through the CAD interface. D. Incremental Update Verification: Based on the node incremental learning algorithm of graph neural network (GNN), only the nodes that have changed in the knowledge base are updated. The accuracy of the update is confirmed by a multi-professional expert collaborative verification module, and a version record with a timestamp is generated.

[0020] The method for constructing a cross-modal knowledge graph schema for electrical design includes the following steps: S1. Define the cross-modal core entity set: construct specification entities, component entities, design scenario entities, selection / wiring rule entities, design error entities, knowledge gap entities, and version entities. Each entity contains a cross-modal mapping field (Map-ID). S2. Entity Attribute Constraints: Configure electrical design-specific core attributes for each entity. Among them, the specification entity includes the standard number, clause content, and cross-modal mapping ID (associated with the drawing verification rule ID); the component entity includes the model, parameters, and drawing mapping ID (unique identifier of CAD component); and the design error entity includes the error type, associated component / circuit ID, and corresponding drawing ID. S3. Cross-modal relationship definition: Establish three exclusive relationships: cross-modal alignment drawings, knowledge mapping specifications, and scenario adaptation. The cross-modal alignment relationship associates the vectorized entities of the drawings with the text knowledge nodes through the mapping ID (Map-ID) generated by the CLIP model, realizing a unique mapping between component model - terminal number - wiring path and component entity - wiring rule - specification basis; S4.Schema Integrity Verification: Verify whether entity attributes and relationship definitions cover the knowledge association requirements of the entire electrical design process through electrical-specific LLM, ensuring 95% accuracy of association when cross-modal data is mutually driven.

[0021] The design error feedback closed-loop module constructs an error collection-root cause analysis-knowledge correction-verification and implementation closed loop, specifically: A. The design software outputs verification errors. Through the verification feedback interface of the CAD design software, verification error data during the electrical design process is received in real time. The error data includes error type (selection error / wiring error / standard compliance error), associated component / circuit ID, error description and corresponding drawing ID; B.LLM Analysis of Error Root Causes: Using electrical-specific LLM to analyze error root causes, matching the corresponding selection rules, wiring rules, or specification clauses in the knowledge base, locating the type of knowledge gap (vague description / outdated content / missing information), and generating gap records; C. Generate update tasks: Based on the type of knowledge gap, automatically generate knowledge base update tasks, including the knowledge node ID to be updated, suggestions for supplementary / corrected content, and relevant regulatory basis. Push them to experts for review, assign corresponding experts according to the professional field of the error, and confirm the accuracy and compliance of the updated content through a dual mechanism of LLM pre-review + expert final review. D. After approval, the knowledge base is automatically updated, automatically synchronized to the knowledge base, and a version traceability chain is generated. At the same time, the design verification rules are optimized through the CAD interface to avoid the recurrence of similar errors.

[0022] The real-time synchronization module for specifications includes a built-in dynamic monitoring and precise replacement module: - It connects to official databases such as GB / T, IEC, and DL / T to capture standard updates in real time (such as the revision of GB 50054-2024). - The LLM module automatically splits and updates clauses, matching the corresponding old clauses in the knowledge base to generate replacement suggestions. + The version traceability chain supports filtering specifications by design scenario (such as building electrical / industrial electrical) to avoid redundant updates.

[0023] The CAD interface protocol specification of the CAD interface interaction module is used to realize bidirectional interaction between CAD design software and the knowledge base dynamic update system, specifically including the following: A. Interface Function Set Definition: Includes data acquisition interface, knowledge push interface, verification feedback interface, and engineering change synchronization interface. These interfaces correspond to the entire process of electrical design selection, drawing, verification, and change, respectively. B. Data transmission specifications: Structured data uses JSON format, vectorized drawing data uses XML format, binary files use Base64 encoding, local communication uses Socket protocol (10ms delay), and cross-device communication uses HTTPS protocol; C. Security Mechanism: It adopts triple protection of device authentication + user token + AES-256 data encryption. Device authentication is verified by hardware SN number, user token is valid for 24 hours, and data transmission encryption key is rotated periodically; D. Error handling mechanism: When the interface call fails, the CAD software caches the data and starts automatic retry. The retry interval is 3 seconds. After 3 failed retries, a manual synchronization prompt is triggered to ensure that no data is lost.

[0024] The specified real-time synchronization engine includes the following core modules: A. Multi-source specification access module: Connects to official data sources such as the Standardization Administration of China (SAC), China Electricity Council (CEC), and International Electrotechnical Commission (IEC), and obtains updated data of GB / T, DL / T, and IEC series electrical specifications in real time through API calls, data subscriptions, or compliant crawling. B. Clause-level Difference Comparison Module: Employs a cosine similarity algorithm combined with electrical domain keyword weighting to compare the clause content of the new and old specifications. It uses an electrical-specific LLM to determine whether the changes are substantial and marks newly added / modified / repeated clauses. C. Precise Replacement and Version Tracking Module: Precisely replaces modified clauses, retaining the old version content and the reason for replacement; marks obsolete clauses with status and retains the original text; associates new clauses with corresponding design scenario tags, generating a traceability chain containing specification number - version - change content - affected project; D. Design Scenario Adaptation Push Module: Filter updated specifications according to the scenario type of electrical design projects (building electrical / industrial electrical / substation), and push specification update notifications and adaptation suggestions to design projects that are using the specification through the CAD interface, prompting designers to check.

[0025] Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art and related fields based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described and explained in the present invention, unless otherwise specified or limited, shall be implemented according to conventional means in the art.

Claims

1. A dynamic update system for an electrical design knowledge base based on a large language model, characterized in that, It includes a cross-modal mutual-driven update module, a design error feedback closed-loop module, a specification real-time synchronization module, a multi-expert collaborative certification module, a knowledge storage module, a CAD interface interaction module, and a large language model processing module; The cross-modal mutual-driven update module is used to realize cross-modal acquisition, alignment and bidirectional mutual-driven update of CAD drawing vector data, text knowledge data and electrical specification data; The design error feedback closed-loop module is used to collect verification error data in the electrical design process, locate knowledge gaps in the knowledge base, generate update tasks, and optimize the knowledge base and design verification rules in a closed loop after expert verification. The aforementioned real-time synchronization engine is used to connect to the official electrical specification data source to achieve clause-level difference comparison, accurate replacement, version tracking, and design scenario adaptation push. The multi-expert collaborative certification module performs LLM pre-verification according to professional sub-review permissions, supports online annotation by multiple people, and automatically summarizes the points of disagreement and generates compromise suggestions. The knowledge storage module adopts a hybrid storage architecture of electrical design-specific knowledge graph + vector library + version library; The CAD interface interaction module is used to establish communication with at least one of AutoCAD Electrical, power design software, and EPLANElectric P8 to realize data acquisition, knowledge push, error feedback, and change synchronization. The large language model processing module adopts a finely tuned large language model from the electrical domain for standardized text splitting, knowledge triple extraction, error root cause analysis, difference change judgment, and expert opinion fusion.

2. The dynamic update system for an electrical design knowledge base based on a large language model according to claim 1, characterized in that, The cross-modal mutual-driven update module constructs an electrical design cross-modal knowledge graph schema. Based on knowledge graph node similarity and vector retrieval, it achieves incremental updates of cross-modal data, avoiding duplication. Specifically: A. Newly added components in drawings will be automatically added to the knowledge graph component library and associated with the corresponding selection specifications; B. Newly added clauses in the text will provide feedback on the drawing verification rules and mark design nodes that do not conform to the new specifications; thus solving the pain point of the lack of synchronization between drawings and textual knowledge.

3. The dynamic updating system for an electrical design knowledge base based on a large language model according to claim 1, characterized in that, The specific functions of the cross-modal mutual drive update module include: A. Cross-modal data acquisition: Through the interface protocol with CAD design software, multi-source data in the entire electrical design process is collected synchronously. The multi-source data includes vectorized data of CAD drawings, component selection text data, electrical specification clause data, and engineering change data. B. Cross-modal data processing: The YOLO object detection algorithm is used to extract component entities, wiring relationships and layout rules from the drawings. The specification text and selection manual are split by a large language model fine-tuned in the electrical field to extract knowledge triples. The CLIP model is used to achieve cross-modal alignment between the vectorized drawing results and the text knowledge nodes. C. Mutual-driven update trigger: When new cross-modal data is collected, if the drawing data adds new components / wiring relationships, the corresponding nodes and relationships in the knowledge graph of the knowledge base will be automatically updated; if the text knowledge is updated, the intelligent annotation and verification rules of the drawing will be optimized through the CAD interface. D. Incremental Update Verification: Based on the node incremental learning algorithm of graph neural network, only the nodes that have changed in the knowledge base are updated. The accuracy of the update is confirmed by a multi-professional expert collaborative verification module, and a version record with a timestamp is generated.

4. The dynamic updating system for an electrical design knowledge base based on a large language model according to claim 2, characterized in that, The method for constructing a cross-modal knowledge graph schema for electrical design includes the following steps: S1. Define the cross-modal core entity set: construct specification entities, component entities, design scenario entities, selection / wiring rule entities, design error entities, knowledge gap entities, and version entities. Each of these entities contains cross-modal mapping fields. S2. Entity Attribute Constraints: Configure electrical design-specific core attributes for each entity. Among them, the specification entity includes the standard number, clause content, and cross-modal mapping ID; the component entity includes the model, parameters, and drawing mapping ID; and the design error entity includes the error type, associated component / circuit ID, and corresponding drawing ID. S3. Cross-modal relationship definition: Establish three exclusive relationships: cross-modal alignment drawing, knowledge mapping specification, and scenario adaptation. The cross-modal alignment relationship associates the vectorized entities of the drawing with the text knowledge nodes through the mapping ID generated by the CLIP model, realizing a unique mapping between component model - terminal number - wiring path and component entity - wiring rule - specification basis; S4.Schema Integrity Verification: Verify whether entity attributes and relationship definitions cover the knowledge association requirements of the entire electrical design process through electrical-specific LLM, ensuring 95% accuracy of association when cross-modal data is mutually driven.

5. The dynamic updating system for an electrical design knowledge base based on a large language model according to claim 1, characterized in that, The design error feedback closed-loop module constructs an error collection-root cause analysis-knowledge correction-verification and implementation closed loop, specifically: A. The software outputs a validation error; B.LLM analyzes the root causes of errors: locating errors in the knowledge base, and identifying vague / outdated descriptions; C. Generate an update task and push it to experts for review; D. After the review is approved, the knowledge base will be automatically updated, and feedback will be provided to the design software to optimize the verification rules.

6. The dynamic updating system for an electrical design knowledge base based on a large language model according to claim 1, characterized in that, The real-time synchronization module for specifications includes a built-in dynamic monitoring and precise replacement module: - It connects to official databases such as GB / T, IEC, and DL / T to capture standard updates in real time. The LLM (Local Standard Model) automatically splits the updated clauses, matches them with the corresponding old clauses in the knowledge base, and generates replacement suggestions. + The version traceability chain supports filtering specifications by design scenario to avoid redundant updates.

7. The dynamic updating system for an electrical design knowledge base based on a large language model according to claim 1, characterized in that, The CAD interface protocol specification of the CAD interface interaction module is used to realize bidirectional interaction between CAD design software and the knowledge base dynamic update system, specifically including the following: A. Interface Function Set Definition: Includes data acquisition interface, knowledge push interface, verification feedback interface, and engineering change synchronization interface. These interfaces correspond to the entire process of electrical design selection, drawing, verification, and change, respectively. B. Data transmission specifications: Structured data uses JSON format, vectorized drawing data uses XML format, binary files use Base64 encoding, local communication uses the Socket protocol, and cross-device communication uses the HTTPS protocol; C. Security Mechanism: It adopts triple protection of device authentication + user token + AES-256 data encryption. Device authentication is verified by hardware SN number, user token is valid for 24 hours, and data transmission encryption key is rotated periodically; D. Error handling mechanism: When the interface call fails, the CAD software caches the data and starts automatic retry. The retry interval is 3 seconds. After 3 failed retries, a manual synchronization prompt is triggered to ensure that no data is lost.

8. The management method of a marketing management system based on AI algorithms according to claim 6, characterized in that, The specified real-time synchronization engine includes the following core modules: A. Multi-source standard access module: Connects to official data sources such as the National Standardization Management Committee, China Electricity Council, and International Electrotechnical Commission, and obtains updated data of GB / T, DL / T, and IEC series electrical standards in real time through API calls, data subscriptions, or compliant crawling. B. Clause-level Difference Comparison Module: Employs a cosine similarity algorithm combined with electrical domain keyword weighting to compare the clause content of the new and old specifications. It uses an electrical-specific LLM to determine whether the changes are substantial and marks newly added / modified / repeated clauses. C. Precise Replacement and Version Tracking Module: Precisely replaces modified clauses, retaining the old version content and the reason for replacement; marks obsolete clauses with status and retains the original text; associates new clauses with corresponding design scenario tags, generating a traceability chain containing specification number - version - change content - affected project; D. Design Scenario Adaptation Push Module: Filter updated specifications according to the scenario type of electrical design projects, and push specification update notifications and adaptation suggestions to design projects that are using the specifications through the CAD interface, prompting designers to check.

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