Application Research of Digital Intelligence Technology in Mining Electric Power Equipment Fault Cases: Taking Text Mining Technology as an Example

Electric power text data offers good mining potential and higher information value. However, the lack of a highly organized information carrier in the text data about electric power makes automated analysis difficult. By outlining the development process and difficulties during implementation of text mining and deep analysis of the characteristics of fault texts, this work proposed text mining framework for typical fault cases of power equipment. Additionally, the realization path of text mining technology contribute to electric power equipment failures is combined with the conventional text mining research in the electric power field. There are four steps in which text mining algorithms are practically applied to text on power outages: named entity recognition, entity relationship extraction, knowledge graph construction, and equipment status assessment. Finally, in view of the grid’s future development, the prospect of text mining for electrical equipment problems is examined. This contribution explores the latest developments and significant difficulties in the field of electric power fault text mining in order to evaluate the strategy of high-quality development of the electric power field enabled by digital intelligence technology.