电力建设2026，Vol.47Issue(7)：113-128,16.DOI:10.12204/j.issn.1000-7229.2026.07.009
基于知识图谱与预训练模型的HVDC故障诊断及运维决策技术
Knowledge Graph and Pre-Trained Model-Based HVDC Fault Diagnosis and Operation and Maintenance Decision-Making Technology
摘要
Abstract
[Objective]Intelligent operation and maintenance(O&M)of high voltage direct current(HVDC)systems face critical challenges,including insufficient accuracy in state assessment,limited predictive foresight in risk assessment,and poor real-time performance in fault diagnosis.Traditional methods are constrained by limitations in multi-source data fusion,small-sample generalization,and decision interpretability.This paper systematically reviews the integration pathways of knowledge graphs and pre-trained models,aiming to provide theoretical references for building a new generation of HVDC intelligent O&M systems.[Methods]First,the technical bottlenecks in three core scenarios—state assessment,risk prediction,and fault diagnosis—are analyzed.Subsequently,the integration fundamentals and synergistic mechanisms of knowledge graphs and pre-trained models are elaborated.Finally,key advancements and solutions applied to these three scenarios are summarized.[Results]The deep integration of knowledge graphs and pre-trained models effectively addresses pain points such as data silos,weak generalization with small samples,and the"black-box"nature of decision-making.Notable breakthroughs have been achieved in multi-modal feature alignment,temporal causal reasoning,and cloud-edge collaborative diagnosis.[Conclusions]However,challenges remain regarding automatic knowledge updating,the integration of physical mechanisms,and real-time assurance.Future research should focus on automated knowledge engineering,physics-informed pre-trained models,and trustworthy evaluation systems.关键词
直流输电/知识图谱/预训练模型/故障诊断/运维决策/云边协同Key words
DC transmission/knowledge graph/pre-trained model/fault diagnosis/operation and maintenance(O&M)decision-making/cloud-edge collaboration分类
信息技术与安全科学引用本文复制引用
张世洪,李强,曹生辉,李应飞,马越,高雨杰,杨博..基于知识图谱与预训练模型的HVDC故障诊断及运维决策技术[J].电力建设,2026,47(7):113-128,16.基金项目
国家自然科学基金项目(62263014) （62263014）
中国南方电网有限责任公司科技项目(CGYKJXM20240120) This work is supported by National Natural Science Foundation of China(No.62263014)and Science and Technology Project of China Southern Power Grid Company Limited(No.CGYKJXM20240120). （CGYKJXM20240120）
