Analysis of knowledge graph of development situation of intelligent operation and maintenance technology in coal mine

CHU Xiaoyu; SHENG Wu

doi:10.19956/j.cnki.ncist.2025.02.009

Abstract：To accurately perceive the development trend of intelligent operation and maintenance technology in the field of coal mine,the text mining knowledge graph approach is employed,relying on the China National Knowledge Infrastructure(CNKI)database.Literature retrieval is conducted using relevant keywords related to intelligent operation and maintenance of coal mines.The CiteSpace visualization bibliometric tool is utilized to construct the knowledge graph,and the situation was perceived from multiple dimensions such as the volume of published papers,core authors,research institutions,research hotspots,and frontier trends.The research indi-cates that the research on intelligent operation and maintenance technology of coal mines is in a rapid growth phase,with a significant increase in the annual volume of published papers.Several core research teams have initially emerged;however,the cooperation among teams is loose,and a core author group has not yet formed.The research hotspots are summarized as coal mine mechanical and electrical equipment,fault diagnosis,state monitoring,health management,online diagnosis,deep learning,remote operation and maintenance,and predic-tive maintenance.Artificial intelligence technology has become the key driving force for the development of the intelligent operation and maintenance field in coal mines.Further exploration of the frontier development trends reveals that the research in this field has phased characteristics,and the various technological hotspots are gradually integrating.Through in-depth applications of big data analysis and machine learning algorithms,suggestions for the application paths of intelligent operation and maintenance technology in coal mines are pro-posed.