大数据分析在变电站通信网络故障诊断中的应用
Application of Big Data Analysis in Fault Diagnosis of Substation Communication Network
陈兴东 1白云海1
作者信息
- 1. 国网河北省电力有限公司超高压分公司,河北 石家庄 050000
- 折叠
摘要
文章主要探讨大数据分析技术在变电站通信网络故障诊断中的应用.详细分析电力通信网络的主要特性与面临的挑战.基于特征工程、机器学习等大数据分析技术提出一套完备的故障诊断流程.通过对特定算法的分析,初步验证了大数据分析方法在故障诊断问题中的有效性.其中,对于通信网络业务流量和链路状态故障诊断的准确率可达 91.7%,推理速度约为 37.7 次/s.结果表明,大数据分析技术能显著提高故障检测的准确性,缩短诊断时间,为变电站通信网络提供强有力的技术支持.
Abstract
This paper mainly discusses the application of big data analysis technology in substation communication network fault diagnosis.The main characteristics and challenges of power communication network are analyzed in detail.A complete set of fault diagnosis process is proposed based on big data analysis technologies such as feature engineering and machine learning.Through the analysis of specific algorithms,this paper preliminarily verifies the effectiveness of big data analysis method in fault diagnosis.Among them,the accuracy of fault diagnosis for traffic and link state of communication network can reach 91.7%,with an inference speed of approximately 37.7 inferences per second.The results show that the big data analysis technology can significantly improve the accuracy of fault detection,reduce the diagnosis time,and provide strong technical support for substation communication network.
关键词
大数据分析/通信网络/故障诊断Key words
big data analysis/communication networks/fault diagnosis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据