摘要
电力设备运维知识架构建设是智能电网体系的重要组成部分,涉及设备状态监测、故障诊断、预测性维护及智能决策优化。文章分析了人工智能(Artificial Intelligence,AI)大模型的基本原理,研究了基于多源数据融合的知识图谱构建方法,提出了AI大模型赋能的自适应学习框架,旨在提升电力设备健康管理的精准度和运维决策的智能化水平。
The construction of the knowledge architecture for power equipment operation and maintenance is an essential component of the smart grid system,involving equipment condition monitoring,fault diagnosis,predictive maintenance,and intelligent decision-making optimization.The paper analyzes the basic principles of artificial intelligence(AI)large models,studies knowledge graph construction methods based on multi-source data fusion,and proposes an AI large model-enabled adaptive learning framework,aiming to improve the accuracy of power equipment health management and the intelligence level of operation and maintenance decision-making.
作者
付海祥
胡凯
FU Haixiang;HU Kai(Nanjing Control System Co.,Ltd.of State Grid NARI,Nanjing Jiangsu 210000,China;Nanjing Branch of Shenzhen Huayun Zhongsheng Technology Co.,Ltd.,Nanjing Jiangsu 210000,China)
出处
《信息与电脑》
2025年第15期16-18,共3页
Information & Computer
关键词
AI大模型
电力设备运维
知识架构
AI large model
power equipment operation and maintenance
knowledge architecture
作者简介
付海祥,男,本科,助理工程师。研究方向:智能运维、云平台。
