摘要
在人工智能背景下,通过监测得到电网中的海量数据对电力设备运行状态进行快速、准确的预测,为后续故障预警打下坚实基础。以人工智能背景下机器学习方法用于变压器故障诊断为研究主题,详细介绍了三类经典的智能诊断模型:神经网络、支持向量机和贝叶斯分类,阐述并总结了这三类智能诊断模型在变压器故障诊断工作中的应用、发展以及相应特点;最后介绍了变压器故障诊断发展趋势,并进行了展望。
In the context of artificial intelligence,by monitoring the massive data in the power grid,the operation status of power equipment can be quickly and accurately predicted,laying a solid foundation for subsequent fault warning.Taking machine learning methods for transformer fault diagnosis in the context of artificial intelligence as the research topic,three classic intelligent diagnostic models are introduced in detail:neural networks,support vector machines,and Bayesian classification.The application and development of these three types of intelligent diagnostic models in transformer fault diagnosis work are elaborated and summarized,as well as their corresponding characteristics;Finally,the development trend of transformer fault diagnosis was introduced and prospects were made.
作者
汤心韵
张淼
邹旻昊
张成林
李思
TANG Xinyun;ZHANG Miao;ZOU Minhao;ZHANG Chenglin;LI Si(State Grid Hunan Electric Power Co.,Ltd.,Technical Skills Training Center(Changsha Electric Power Vocational and Technical College),Changsha 410131,China;Zhangjiajie Power Supply Company of State Grid Hunan Electric Power Co.,Ltd.,Zhangjiajie 427000,China;State Grid Henan Electric Power Co.Ltd.Fangcheng County Power Supply Company,Nanyang 473200,China)
出处
《电气应用》
2023年第9期69-76,共8页
Electrotechnical Application
关键词
人工智能
机器学习
变压器故障诊断
智能诊断模型
artificial intelligence
machine learning
transformer fault diagnosis
intelligent diagnostic model
