Research and application of knowledge graph construction for wind turbine operation and maintenance

被引：0
|
作者：
Huang J. [1 ]
Yang C. [1 ]
Feng T. [2 ]
Sun N. [3 ]
Li J. [1 ]
Yu H. [1 ]
Cui H. [1 ]
机构：
[1] College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai
[2] State Grid Shanghai Electric Power Company, Information and Communication Company, Shanghai
[3] Training Center of State Grid Shanghai Municipal Electric Power Company, Shanghai
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2024年 / 52卷 / 08期
基金：
中国国家自然科学基金;
关键词：
knowledge graph; Neo4j diagram database; TextRank algorithm; wind turbine operation and maintenance;
D O I：
10.19783/j.cnki.pspc.230950
中图分类号：
学科分类号：
摘要：
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. © 2024 Power System Protection and Control Press. All rights reserved.
引用
下载
收藏
页码：167 / 177
页数：10
相关论文
共 27 条
  • [1] HUANG Lingling, FU Yang, REN Haohan, Et al., Review of wind turbine maintenance based on condition monitoring systems, Proceedings of the CSEE, 40, 21, pp. 7065-7078, (2020)
  • [2] LIU Jun, AN Bairen, ZHANG Weibo, Et al., Review of health status evaluation of large wind turbines, Power System Protection and Control, 51, 1, pp. 176-187, (2023)
  • [3] YANG Li, LI Gaoyang, ZHANG Zihan, Et al., Operations & maintenance optimization of wind turbines integrating wind and aging information, IEEE Transactions on Sustainable Energy, 12, 1, pp. 211-221, (2020)
  • [4] LI Qingmin, YU Wanshui, ZHAO Jiyao, Key technologies for the safe operation of wind and solar power generation equipment in support of the “peak CO<sub>2</sub> emissions and carbon neutrality” policy, High Voltage Engineering, 47, 9, pp. 3047-3060, (2021)
  • [5] GUYEN N, ALMASABI S, MITRA J., Impact of correlation between wind speed and turbine availability on wind farm reliability, IEEE Transactions on Industry Applications, 55, 3, pp. 2392-2400, (2019)
  • [6] DONG Hongyang, ZHAO Xiaowei, Data-driven wind farm control via multiplayer deep reinforcement learning, IEEE Transactions on Control Systems Technology, 31, 3, pp. 1468-1475, (2023)
  • [7] TIAN Meng, WU Jinfang, YANG Lin, Et al., Practice of wind farm operation and maintenance management system construction, Electric Safety Technology, 22, 7, pp. 25-28, (2022)
  • [8] GUO Rong, YANG Qun, LIU Shaohan, Et al., Construction and application of power grid fault handing knowledge graph, Power System Technology, 45, 6, pp. 2092-2100, (2021)
  • [9] CHEN Yongrui, LI Huiying, QI Guilin, Et al., Outlining and filling: hierarchical query graph generation for answering complex questions over knowledge graphs, IEEE Transactions on Knowledge and Data Engineering, 35, 8, pp. 8343-8357, (2023)
  • [10] QIAO Ji, WANG Xinying, MIN Rui, Et al., Framework and key technologies of knowledge-graph-based fault handling system in power grid, Proceedings of the CSEE, 40, 18, pp. 5837-5849, (2020)
123