基于语义分析的设备监控告警信息知识图谱构建研究

Study on Knowledge Graph Construction of Equipment Monitoring and Alarming Information Based on Semantic Analysis

为实现对SCADA(数据采集与监控)系统海量告警信息的智能化辨识和分析,提出了一种面向电力设备监控告警信息故障诊断辅助决策的知识图谱构建方法。在构建电网设备知识图谱的基础上,将基于改进BM(Boyer-Moore)算法的语义分析技术与结线分析方法相结合,对告警信息进行智能化字符解析,形成可供决策系统辨识的结构化知识网络;利用推理引擎查询匹配的知识路径,进行告警信息判断和分析。通过某110 kV线路故障跳闸案例分析表明,所提方法实现了基于知识图谱的故障告警信息解析判别和智能辅助决策,为设备监控人员故障快速处理提供了参考。

The paper proposes a knowledge graph construction method for power equipment monitoring and alarming information fault diagnosis and decision-making support for intelligent recognition and analysis of massive alarming information from SCADA(supervisory control and data acquisition)system.By knowledge graph construction of power grid equipment,the semantic analysis technology based on the improved BM(Boyer-Moore)algorithm and the connection analysis method are combined for intelligent character analysis of the alarming information to obtain a structured knowledge network that can be recognized by the decision-making system;the inference engine is used to search the matched knowledge path to judge and analyze the alarming information.Through a 110 kV line fault trip analysis,it is demonstrated that the proposed method enables fault alarming information analysis and intelligent decision-making based on knowledge graph and can provide equipment monitoring personnel with reference to fast fault handling.