首页|知识图谱在输变电设备运维中的应用

知识图谱在输变电设备运维中的应用

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对输变电设备海量数据进行有效利用和管理是新型电力系统信息化发展的重要方向,挖掘电网输变电设备运维数据,并感知其运行态势,可保障输变电设备安全稳定的运行.该文将知识图谱引入输变电设备运维领域,分析输变电设备运维的数据情况和现存问题;介绍输变电设备数据融合聚类技术和运维知识图谱的构建技术;结合输变电设备运维特性,总结知识图谱在输变电设备运维中的典型应用场景;分析当前研究热点,探讨知识图谱在输变电设备运维领域的关键问题,并展望该领域的发展前景.运用知识图谱,在提高企业维修效率的同时,还能降低人力成本.
Application of Knowledge Graph in Operation and Maintenance of Power Transmission Equipment
Effective utilization and management of the massive data of transmission and transformation equipment is an important direction for the development of new power system informatization.Mining the O&M data of transmission and transformation equipment and perceiving its situation can ensure the safe and stable operation of these equipment.Therefore,this paper introduces knowledge graphs into the field of the transmission and transformation equipment O&M field.First,the data and existing problems of the transmission and transformation equipment O&M service are analyzed.Second,the data fusion and clustering technology of transmission and transformation equipment and the construction technology of the O&M knowledge graph are introduced.Third,combined with the O&M characteristics of transmission and transformation equipment,the typical application scenarios of the knowledge graph in the O&M service of transmission and transformation equipment are summarized.Finally,the current research hot spots are analyzed,the key issues of knowledge graphs in the transmission and transformation equipment O&M field are discussed with the development prospect of this field presented.The use of knowledge mapping in the field of transmission and substation operation and maintenance not only improves the maintenance efficiency of the enterprise,but also reduces the manpower cost.

knowledge graphpower transmission and transformation equipmentartificial intelligence

饶桐、龚泽威一、于虹、王钢、骆钊、朱家祥

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云南电网有限责任公司电力科学研究院,云南昆明 650217

昆明理工大学电力工程学院,云南昆明 650500

知识图谱 输变电设备 人工智能

国家自然科学基金项目云南省应用基础研究计划项目云南电网有限责任公司科技项目

51907084202101AT070080YNKJXM20220011

2024

电网与清洁能源
西北电网有限公司 西安理工大学水电土木建筑研究设计院

电网与清洁能源

CSTPCD北大核心
影响因子:1.122
ISSN:1674-3814
年,卷(期):2024.40(6)
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