综合智慧能源 ›› 2024, Vol. 46 ›› Issue (1): 65-74.doi: 10.3969/j.issn.2097-0706.2024.01.008
蔺家骏1(), 闫玮丹2,*(), 胡俊华3, 郑一鸣1, 邵先军1, 郭炳延2
收稿日期:
2022-09-27
修回日期:
2023-04-03
出版日期:
2024-01-25
发布日期:
2023-05-05
通讯作者:
*闫玮丹(2000),女,博士生,从事电力领域的多模态知识图谱技术等方面的研究,作者简介:
蔺家骏(1990),男,高级工程师,博士,从事变电设备管理与分析、电力运检知识图谱等方面的工作,linjiajun_zjdl@163.com。
基金资助:
LIN Jiajun1(), YAN Weidan2,*(), HU Junhua3, ZHENG Yiming1, SHAO Xianjun1, GUO Bingyan2
Received:
2022-09-27
Revised:
2023-04-03
Online:
2024-01-25
Published:
2023-05-05
Supported by:
摘要:
在构建以新能源为主体的新型电力系统背景下,知识图谱(KG)作为可视化的大型语义网络在电力运检中的应用处于快速发展阶段。近年来,KG在电力运检的应用主要集中在语义信息方面,然而电网运行中会产生大量异构数据,足以支撑构建多模态知识图谱(MMKG),为多种下游任务提供数据支持。从电力运检的功能需求出发提出引入MMKG解决综合智能问答系统和故障处置问题,重点介绍了针对电力运检数据的MMKG构建技术,总结了MMKG能够发挥作用的电力运检功能场景,并对未来发展方向做出展望,最后深入分析了发展MMKG会面临的挑战,为电力运检智能化发展与建设提供参考。
中图分类号:
蔺家骏, 闫玮丹, 胡俊华, 郑一鸣, 邵先军, 郭炳延. 多模态知识图谱在电力运检中的应用与展望[J]. 综合智慧能源, 2024, 46(1): 65-74.
LIN Jiajun, YAN Weidan, HU Junhua, ZHENG Yiming, SHAO Xianjun, GUO Bingyan. Application and prospect of multimodal knowledge graph in electric power operation inspection[J]. Integrated Intelligent Energy, 2024, 46(1): 65-74.
表1
典型KG
KG名称 | 数据规模 | 适用 领域 |
---|---|---|
Freebase | 6 800万个实例,24亿个三元组 | 通用 |
Dbpedia | 40亿个实体,2 800万个知识联系,95亿个三元组 | 通用 |
YAGO | 980万个实体,114个知识联系,4.5亿个三元组 | 通用 |
Zhishi.me | 超1 200万个实例,超1.2亿个三元组 | 通用 |
XLORE | 66万个实体,5万个属性,1 000万个实例 | 通用 |
Google Knowledge Graph | 5.8亿个实体,3.5万个知识联系,180亿个三元组 | 通用 |
开源军事武器装备KG | 武器类实体5 800个,实体属性关系184类,实体上位关系1类,包括8大类、148小类的武器装备,涉及国家88个 | 军事 |
Linked Movie Dataset | 61.5万个三元组数据 | 影视 |
乳腺癌KG | 超过2 200万个三元组 | 医学 |
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