Research on Transformer Inter-Turn Short Circuit Fault Identification Based on Knowledge Map
The correlation between the fault data appearing in the transformer is not well utilized,which will directly affect the accuracy of transformer inter-turn short circuit fault identification.For this reason,research on transformer inter-turn short circuit fault identification based on knowledge map is proposed.Based on the flexible strategy to collect transformer data,the amount of data collection and time interval are adjusted according to the actual operating conditions and data collection target demand.Based on the collected transformer data,the knowledge map is constructed using the steps of ontology construction,entity extraction,relationship extraction and map construction.The extracted knowledge map fault sample features are input into the you only look once(YOLO)v4 detection model.The automatic identification of transformer inter-turn short circuit faults is accomplished by the detection method combining the YOLOv4 detection model and the knowledge map.The test results show that the accuracy,recall and F-value of automatic transformer inter-turn short circuit fault identification are high,so the identification timeliness is high,and the automatic identification effect is good.The research solves the problems existing in the traditional method,and has important practical significance.
Knowledge mapTransformerInter-turn short circuit faultsEntity extractionYou only look once(YOLO)v4 detection modelFlexible strategyRelational extraction