Partial Discharge Defect Detection Method of Insulation Equipment Based on Knowledge Map

To improve the accuracy of insulation state detection of power equipment, an intelligent method for power defect information processing using knowledge map technology is proposed in this paper. By optimizing the general process of constructing knowledge map, this scheme proposes to use graph search to identify defects and record errors. To improve the utilization of data and mine the related information affecting the insulation state of equipment, Neo4j's power big data modeling method is used to store the text data of insulation state of power equipment based on graph database. The experimental results show that the insulation equipment defect detection based on graph database and knowledge map has high recognition efficiency and meets the real-time requirements of the system.