内蒙古电力技术2025，Vol.43Issue(5)：23-29,7.DOI:10.19929/j.cnki.nmgdljs.2025.0057
电力作业风险预控知识图谱构建与应用研究
Research on Construction and Application of Knowledge Graph of Risk Pre-Control in Electric Power Operation
摘要
Abstract
This paper proposes a strategy for constructing a knowledge graph for pre-control of power operation risks based on bidirectional encoder representations from transformers(BERT)technology,aiming to significantly enhance the safety and efficiency of power operations through intelligent means.Firstly,a training dataset specifically for the risk domain of power operation is constructed.Secondly,the BERT-BILSTM-CRF(where BILSTM stands for bidirectional long short-term Memory,and CRF stands for conditional random field)model is used to identify the entities related to transformer operation and maintenance.Furthermore,the BERT-BILSTM-Attention model is used to effectively recognize the relationships between entities.The performance of these two models are demonstrated through comparative experimental results.Finally,686 entities and 720 entity relationships are successfully imported into the Neo4j graph database,achieving intuitive visualization of the knowledge graph.On this basis,auxiliary decision-making functions are developed.关键词
电力作业风险预控/知识图谱/BERT-BILSTM-CRF/Neo4j图数据库Key words
power operation risk pre-control/knowledge graph/BERT-BILSTM-CRF/Neo4j graph database分类
信息技术与安全科学引用本文复制引用
阿敏夫,孙彪,武鹏飞,赵亚鑫..电力作业风险预控知识图谱构建与应用研究[J].内蒙古电力技术,2025,43(5):23-29,7.基金项目
内蒙古电力(集团)有限责任公司科技项目"人工智能自学习风险预判算法在现场安全管控中的关键技术研究与应用"(2023-5-33) （集团）
