面向变电站倒闸操作的智能防误知识图谱的构建及应用OA

To address the problems that current operation tickets lack effective anti-misoperation verification means and suffer from low intelligence level,a knowledge-graph construction method for intelligent anti-misoperation of substation switching operations is proposed.Firstly,using professional corpus data of power grid equipment,a deep learning model training method is adopted to construct a power grid equipment connection relationship graph,an error prevention regulation graph,and a historical operation ticket graph,and automatically fuse them to form an intelligent error prevention knowledge graph.Then,experiments are designed to verify the effectiveness of the error prevention model,with an F1 value of 80%and an accuracy rate of 95%.Finally,the intelligent anti-misoperation knowledge graph is managed with high-level visualization by adopting the Neo4j graph database,and the corresponding whole-process application workflow is provided,which effectively improves operators'emergency-handling capabilities when encountering switching-operation faults.