Open AccessResearch on Knowledge Graph Construction for Intelligent Operation and Maintenance of Electrical Transformers
Author(s) -
Bowen Zhang,
Fei Gao,
Ning Yang,
Chengbo Hu,
Ziquan Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1971/1/012013
Subject(s) - computer science , transformer , knowledge graph , knowledge representation and reasoning , knowledge extraction , natural language understanding , semantic web , unstructured data , natural language , artificial intelligence , engineering , big data , data mining , electrical engineering , voltage
In the process of transformer equipment operation and maintenance, power companies encounter some problems, including of unstructured text data difficult to use, full caliber data difficult to deeply integrate and shallow equipment knowledge application. Based on artificial intelligence technology such as semantic web, knowledge map, natural language processing, etc., this paper studies the key technologies of equipment intelligent service, and proposes a knowledge intelligent technology framework for transformer. This framework includes three components: unstructured text intelligent recognition and extraction, device centered device knowledge representation and storage, and device knowledge intelligent application.