The high-frequency operation and maintenance information of large-scale wind turbines increasingly presents the characteristics of high data dimension, interconnection between classes and scale increase. It is difficult to adapt he traditional artificial island-type fault repair and maintenance mode to the integrated development process of a man-machine, material, method and environment. For active operation and maintenance of all links and elements of wind turbines, a method to construct a knowledge graph of operation and maintenance of wind turbines is proposed. This integrates knowledge rules, master-slave equipment, specifications and regulations. TextRank is used to complete entity identification and relationship extraction of wind power professional operation and maintenance text to improve the extraction accuracy of feature words. The Neo4j database is used to construct wind power safety regulation and equipment diagrams to realize the interconnection and visualization of multivariate data, and then realize the intelligent query of wind power operation and maintenance information. In this paper, 629 entities and 742 relationship types of wind turbine knowledge graphs are constructed using the above method. The data query test shows that the accuracy rate and recall rate of the proposed method are all above 89%, which is 6.5% higher than the traditional database method. This method establishes the visual expression of operation and maintenance requirements and the task correlation between classes. Effective inquiry of massive equipment information is helpful to saving the maintenance force of the wind power in the two-carbon strategy and improve the intelligent level of the operation and maintenance.