Intelligent Diagnosis of Substation Equipment Faults Based on Deep Learning and Knowledge Graph
A multi-modal information fault diagnosis method for the associated power equipment was proposed based on deep learning network and knowledge graph technology.The collected data was extracted and fused to construct a knowledge graph of multimodal information.The YOLOv4 algorithm was used to extract the prior box parameters of the electrical equipment fault library.The multimodal information knowledge graph was combined with the YOLOv4 algorithm for visual detection and applied to the diagnosis of main electrical equipment faults.The experimental results show that the proposed method can achieve intelligent diagnosis of main electrical equipment faults,with an accuracy improvement about 18.2％compared to that of other diagnostic algorithms,and can raise the efficiency of power grid operation and maintenance.
deep learningknowledge graphmultimodalelectrical equipmentintelligent diagnosis
万方数据
维普
