知识图谱在装备故障诊断领域的研究与应用综述  

Overview of research and application of knowledge graph in equipment fault diagnosis

作　　者：武杰 张安思 吴茂东 张仪宗 王从宝 WU Jie;ZHANG Ansi;WU Maodong;ZHANG Yizong;WANG Congbao(State Key Laboratory of Public Big Data(Guizhou University),Guiyang Guizhou 550025,China;School of Mechanical Engineering,Guizhou University,Guiyang Guizhou 550025,China;Unit 75841 of Chinese People’s Liberation Army,Guiyang Guizhou 550000,China)

机构地区：[1]公共大数据国家重点实验室(贵州大学),贵阳550025 [2]贵州大学机械工程学院,贵阳550025 [3]中国人民解放军75841部队,贵阳550000

出　　处：《计算机应用》2024年第9期2651-2659,共9页journal of Computer Applications

基　　金：国家重点研发计划项目(2020YFB1713300);国家自然科学基金资助项目(52365061);贵州省科技计划项目(黔科合基础-ZK[2023]一般059);贵州省教育厅高等学校集成攻关大平台项目(黔教合KY字[2020]005)。

摘　　要：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的构建框架;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,提出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。Useful knowledge can be extracted from equipment fault diagnosis data for construction of a knowledge graph,which can effectively manage complex equipment fault diagnosis information in the form of triples(entity,relationship,entity).This enables the rapid diagnosis of equipment faults.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 at home and abroad about several key technologies,such as knowledge extraction,knowledge fusion and knowledge reasoning for equipment fault diagnosis knowledge graph,was summarized.Finally,the applications of knowledge graph in equipment fault diagnosis were summarized,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.

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 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]