A wind turbine operation and maintenance management method based on a knowledge graph

By constructing a wind turbine operation and maintenance knowledge graph using an improved TextRank algorithm and the Neo4j database, the problem of insufficient semantic understanding was solved, enabling efficient operation and maintenance management and fault classification, and improving the intelligence level of wind farms.

CN116775895BActive Publication Date: 2026-06-23SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Patent Information

Application Number
CN202310539483.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-05-12
Publication Date
2026-06-23
Estimated Expiration
2043-05-12

AI Technical Summary

Technical Problem

Existing technologies for wind turbine operation and maintenance management suffer from insufficient semantic understanding capabilities and inaccurate keyword positioning. Furthermore, they lack effective operation and maintenance fault classification and recommendation strategies, resulting in a high proportion of improper operation and maintenance incidents.

Method used

An improved TextRank-based rule-matching algorithm is used to extract entity words, and entity relationships are extracted by combining the rule-matching algorithm. A knowledge graph of safety management procedures and equipment operation and maintenance requirements is constructed, and the Neo4j graph database is used for visualization and intelligent querying to achieve efficient decision-making in operation and maintenance management.

Benefits of technology

It improves the informatization and intelligence level of wind farm operation and maintenance, accurately extracts entity terms, quickly accesses knowledge graphs, provides guidance on operation and maintenance standards, and enhances the efficiency and accuracy of operation and maintenance management.

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Abstract

The application provides a wind turbine operation and maintenance management method based on a knowledge graph, comprising the following steps: performing text content and feature analysis and preprocessing, dividing entity types according to the similarities and differences of entity properties, giving constraint definitions for the relationships of entity types at various levels, and extracting entity words for wind farm operation and maintenance by using a rule matching algorithm based on an improved TextRank; defining the relationships between various entities according to field texts, and realizing the relationship linkage between different entities by using an entity relationship extraction algorithm based on rule matching; constructing a safety management procedure graph and a device operation and maintenance requirement graph established based on a protégé wind power equipment ontology instance topological relationship library; realizing the visualization of the knowledge graph for wind turbine operation and maintenance management, and forming an application scheme by using a query language and a graph embedding technology. Compared with the prior art, the application has the advantages of high accuracy, high efficiency and strong field professional application.
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