The invention belongs to the technical field of
knowledge graph construction, and particularly relates to a
transformer operation inspection-oriented causal relationship enhanced
knowledge graph construction method and
system. According to the method, information in a
transformer fault
processing text is deeply mined, a
natural language processing technology and a
deep learning algorithm are utilized, and accurate recognition and relation extraction of key entities such as fault description, reasons, phenomena, detection methods, detection results and operation and maintenance suggestions are achieved. Structured knowledge is organized and stored in a
graph database, and a comprehensive, deep and easy-to-query
transformer fault operation and maintenance
knowledge graph is formed. By introducing a causal
scientific theory, the causal relationship in the knowledge graph is remarkably enhanced, fault operation and maintenance causal knowledge with a more stable causal effect is formed, the accuracy and robustness of the causal relationship in the knowledge graph are improved, and operation and maintenance personnel can more intuitively understand complex association between fault phenomena and reasons.