电力信息系统网络数据的实时流量监控分析

Real-time traffic monitoring and analysis of network data in power information system

针对当前电力信息系统流量数据监控准确性差、供电不稳定性,易发生流量拥塞等难题,提出一种新型的电力信息系统网络数据流量监控方法,首先采用非线性特征分解方法进行网络流量数据重组,然后采用自适应频谱检测方法实现电力信息系统网络流量数据的谱分析,提取流量数据的谱特征量,最后利用匹配滤波检测器对异常流量进行盲分离处理,实现流量有效监控。仿真结果表明,文中方法使得电力信息系统网络数据流量监控具有实时性和准确性,提高了网络供电的稳定性。

In view of the network traffic data forecast accuracy of the large scale power information system is not good, the power supply stability is not high, and the power information system network is prone to the problem of traffic congestion, so it is necessary to carry out flow monitoring to improve the power supply stability. In this paper, a new method of network data flow monitoring in power information system is proposed. The nonlinear characteristic decomposition method is used to reorganize the network traffic data. Combined with the adaptive spectrum detection method, the spectral analysis of the network traffic data in power information system is carried out, and the spectral characteristics of the traffic data are extracted. Finally, the blind separation of abnormal traffic is carried out by using the matched filter detector. The simulation results show that, this method is used to monitor network data flow of electric power information system with real time and accuracy, and improves the stability of network power supply.