Intelligent Diagnosis Method of Power Communication Equipment Faults Based on Knowledge Graph
As the informationization construction of the State Grid developes rapidly,and the operation and troubleshooting of power communication equipment are becoming increasingly complex.Therefore an intelligent diagnosis method for power communication equipment faults based on knowledge graph is proposed.Firstly,the BERT-BiGRU-CRF(bidirectional encoder representations from transformers-bidirectional gated recurrent unit-conditional random fields)model and artificial rules are utilized to extract fault information entities and relationships.After constructing the knowledge graph of power communication equipment,the WBLA model is used to determine the fault severity and plan the processing sequence.Subsequently,the TFIDF-cos(term frequency-inverse document frequency cosine similarity)method is used to obtain high-confidence fault processing results and realize the intelligent diagnosis of power communication equipment faults.Experiments demonstrate that the accuracy of the method reaches 98.4％and 97.5％respectively,which verifies the feasibility in realizing efficient intelligent diagnosis of power communication equipment faults.
knowledge graphpower communication devicesfault diagnosisintelligent processing
万方数据
维普
