Abstract: Using big data management system to manage coal mine equipment maintenance information lacks the ability to express coal mine equipment maintenance knowledge, has not formed a relatively complete coal mine equipment maintenance knowledge management system, and cannot realize knowledge mining and inter-knowledge relationship links, resulting in a large number of information with in-depthmining value cannot be usedeffectively.In order to solve the above problems, a coal mine equipment maintenance knowledge graph is constructed. Firstly, ontology-based knowledge modeling is carried out by defining key concepts, relationships and attributes of coal mine equipment maintenance. Secondly, obtain knowledge from structured, semi-structured and unstructured data sources, and coal mine equipment maintenance knowledge extraction is completed through named entity identification, relationship extraction and event extraction.Finally, the graph databaseNeo4jis used to store coal mine equipment maintenance knowledge and form a coal mine equipment maintenance knowledge graph.The application of coal mine equipment maintenance knowledge graph in intelligent semantic search, intelligent question and answer and visualization decision support can improve the efficiency of coal mine equipment maintenance knowledge management and provide strong support for the realization of intelligent dynamic management of coal mine equipment.