摘要
针对220 kV变电站故障诊断与处理的重大需求,提出融合设备物理机理与人工智能的混合诊断框架。通过解析变压器、GIS设备等关键组件的多物理场耦合故障机理,构建包含振动频谱、油色谱、局部放电等多维特征参量的感知体系,并创新性引入迁移学习与动态增量算法破解小样本数据下的诊断难题。案例分析表明,所提方法对主变油色谱异常、GIS金属颗粒放电等典型故障的诊断准确率达95.2%,定位效率较传统手段提升了42%。进一步从感知层优化、算法层升级、管理层重构三个维度提出改进措施,开发的可解释性诊断模块与数字孪生培训平台,在试点应用中使运维人员决策效率提升55%,预防性检修比例提高至62%。研究成果为智能变电站运维提供了理论支撑与技术路径,对保障新型电力系统安全运行具有工程实践价值。
This article proposes a hybrid diagnostic framework that integrates equipment physical mechanisms and artificial intelligence to meet the significant demand for fault diagnosis and processing in 220 kV substations.By analyzing the multi physics coupling fault mechanism of key components such as transformers and GIS equipment,a perception system is constructed that includes multidimensional characteristic parameters such as vibration spectrum,oil color spectrum,and partial discharge.Innovative transfer learning and dynamic incremental algorithms are introduced to solve the diagnosis problem in small sample data.Case analysis shows that the proposed method has a diagnostic accuracy of 95.2%for typical faults such as abnormal oil chromatography and GIS metal particle discharge,and a localization efficiency improvement of 42%compared to traditional methods.Further improvement measures are proposed from three dimensions:optimization of perception layer,upgrading of algorithm layer,and reconstruction of management layer.The interpretable diagnostic module and digital twin training platform developed have improved the decision-making efficiency of operation and maintenance personnel by 55%and increased the proportion of preventive maintenance to 62%in pilot applications.The research results provide theoretical support and technical path for the operation and maintenance of intelligent substations,and have engineering practical value for ensuring the safe operation of new power systems.
作者
邵鹤明
石磊
任思成
SHAO Heming;SHI Lei;REN Sicheng(State Grid Jiangsu Electric Power Co.,Ltd.Suzhou Power Supply Branch,Suzhou 215000,China)
出处
《电工技术》
2025年第S1期411-414,共4页
Electric Engineering
关键词
220
kV变电站
故障诊断
混合诊断框架
多维感知
智能运维
220 kV substation
fault diagnosis
hybrid diagnostic framework
multidimensional perception
intelligent operation and maintenance
