基于大数据的继电保护通信系统故障定位方法研究

Research on Fault Location Method of Relay Protection Communication System Based on Big Data

文章针对继电保护通信系统错综复杂和故障定位困难的问题,提出一种基于大数据的继电保护通信系统故障定位方法。该方法设计包括故障信息管理、贝叶斯网络模型处理、故障概率计算以及通信资源管控4个模块,利用大数据技术实现海量异构数据的高效存储与处理,通过贝叶斯网络模型融合多源信息,精准推理故障原因,并依据故障诊断结果实时调配通信资源。仿真实验表明,该方法在故障定位的准确性和实时性方面显著优于传统方法,为提升继电保护通信系统的可靠性提供新的解决方案。

The article proposes a big data based fault localization method for relay protection communication systems,addressing the complex and difficult problems of fault localization.This method design includes four modules:fault information management,Bayesian network model processing,fault probability calculation,and communication resource control.It utilizes big data technology to efficiently store and process massive heterogeneous data.The Bayesian network model integrates multiple sources of information,accurately infers the cause of faults,and allocates communication resources in real-time based on fault diagnosis results.Simulation experiments show that this method is significantly superior to traditional methods in terms of accuracy and real-time performance in fault localization,providing a new solution for improving the reliability of relay protection communication systems.