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基于知识图谱的核电设备健康管理知识建模与分析
引用本文:熊奥,高畅,赵明辉,张玲玲.基于知识图谱的核电设备健康管理知识建模与分析[J].科技促进发展,2021,17(4):640-649.
作者姓名:熊奥  高畅  赵明辉  张玲玲
作者单位:中国科学院大学经济与管理学院 北京 100190;中国科学院大数据挖掘与知识管理重点实验室 北京 100190;中国科学院大学中丹学院 北京 100190
基金项目:年国家自然科学基金面上项目(71471169):基于领域知识和链路预测的个性化推荐研究,负责人:张玲玲; 2020年国家自然科学基金面上项目(72071194):基于知识图谱和链路预测的推荐系统及在设备健康管理中的应用研究,负责人:张玲玲。
摘    要:随着信息技术发展,设备健康数据与知识图谱技术结合为设备健康发展带来新的发展机遇,知识图谱利用其多种特异性优势,使企业系统中积累的海量设备维修数据得到有效整合利用.本文提出基于知识图谱的核电设备健康管理知识建模与分析方法,并根据实体关系模型构建维修知识图谱本体框架,同时基于核电企业实际的维修工单数据,从统计分析和关联分析两方面取得良好的实践效果.研究结果表明,知识图谱能够在设备维修知识的集成上解决传统的数据孤岛问题,同时能基于故障的可视化分析为维修人员和管理人员提供决策和知识支持.

关 键 词:设备健康管理  知识图谱  知识建模  图数据库
收稿时间:2020/10/15 0:00:00
修稿时间:2020/11/16 0:00:00

Knowledge Graph-Based Knowledge Modeling and Analysis for Nuclear Power Equipment Health Management
Xiong Ao,Gao Chang,Zhao Minghui and Zhang Lingling.Knowledge Graph-Based Knowledge Modeling and Analysis for Nuclear Power Equipment Health Management[J].Science & Technology for Development,2021,17(4):640-649.
Authors:Xiong Ao  Gao Chang  Zhao Minghui and Zhang Lingling
Institution:School of Economics and Management, University of Chinese Academy of Sciences,Sino-Danish College, University of Chinese Academy of Sciences,School of Economics and Management, University of Chinese Academy of Sciences,School of Economics and Management, University of Chinese Academy of Sciences
Abstract:With the development of information technology, the combination of equipment health data and knowledge graph technology brings new opportunities for the healthy development of equipment. Knowledge graph makes use of its various specific advantages to effectively integrate and utilize the massive equipment maintenance data accumulated in the enterprise system. This paper proposes a knowledge modeling and analysis method of nuclear power equipment health management based on knowledge graph, and constructs the ontology framework of maintenance knowledge graph according to entity relationship model. At the same time, based on the actual maintenance work order data of nuclear power enterprises, good practice results are achieved from two aspects of statistical analysis and correlation analysis. The results show that the knowledge graph can solve the traditional data island problem in the integration of equipment maintenance knowledge, and provide decision-making and knowledge support for maintenance personnel and management personnel based on the visualization analysis of fault.
Keywords:equipment health management  knowledge graph  knowledge modeling  graph database
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