Abstract: With the continuous development of science and technology, the construction of knowledge graph has been attracted more and more attention. Useful knowledge is extracted from equipment failure diagnosis data for construction of a knowledge graph, which effectively managed complex equipment failure diagnosis information in the form of triples (entity, relationship, entity). This enabled the rapid diagnosis of equipment failures. Firstly, the related concepts of knowledge graph for equipment fault diagnosis were introduced, and the framework of knowledge graph for equipment fault diagnosis domain was analyzed. Secondly, the research status of several key technologies such as knowledge extraction, knowledge fusion and knowledge reasoning for equipment fault diagnosis knowledge graph was summarized. Finally, the application of knowledge graph in equipment fault diagnosis was summarized, and some shortcomings and challenges in the construction of knowledge graph in this field were proposed, and some new ideas were provided for the field of equipment fault diagnosis in the future.

Key words: knowledge graph, equipment fault diagnosis, knowledge graph construction, knowledge reasoning, knowledge extraction

摘要： 随着科学技术的不断发展，知识图谱构建越来越受到关注。知识图谱从装备故障诊断数据中提取有用的知识，通过（实体，关系，实体）的三元组方式，对复杂装备的故障诊断信息进行有效管理，实现装备故障的快速诊断。首先介绍装备故障诊断知识图谱的相关概念，分析装备故障诊断领域知识图谱构建框架；其次，归纳国内外装备故障诊断知识图谱的知识抽取、知识融合以及知识推理等几个关键技术的研究现状；最后，对目前装备故障诊断知识图谱应用进行总结，并提出几点该领域知识图谱构建的不足和面临的挑战，并对未来装备故障诊断领域提供一些新的思路。

关键词: 知识图谱, 装备故障诊断, 知识图谱构建, 知识推理, 知识抽取