fault diagnosis event knowledge graph

We organized and collected two years' worth of complete fault work orders from a wind farm, and structured these work orders into a fault diagnosis event knowledge graph using the proposed algorithm. This graph includes fault modes, fault impacts, fault symptoms, inspection schemes, root cause identification, and maintenance strategies, covering all potential fault information and handling methods for wind turbines. This dataset records the head entity-relation-tail entity information in the form of triples using JSON format. The head and tail entities correspond to fault-related event information, such as fault symptoms at the time of occurrence and fault-handling schemes, while the relation information encompasses the logical relationships between all events, covering the entire process from the onset of the fault to its resolution.