基于CUSUM算法的变电站通信干扰检测研究  

Research on Communication Interference Detection in Substations Based on CUSUM Algorithm

在线阅读下载全文

作  者:宋远 刘欣 成思晋 郭玉福 刘春生 郑存龙 SONG Yuan;LIU Xin;CHENG Sijin;GUO Yufu;LIU Chunsheng;ZHENG Cunlong(State Grid Jilin Electric Power Company Limited,Changchun 130021,China;Construction Branch of State Grid Jilin Electric Power Company Limited,Changchun 130021,China)

机构地区:[1]国网吉林省电力有限公司,吉林长春130021 [2]国网吉林省电力有限公司建设分公司,吉林长春130021

出  处:《微型电脑应用》2024年第9期69-72,共4页Microcomputer Applications

基  金:国网吉林省电力有限公司智慧变电站建设关键技术科技基金项目(522371210003)。

摘  要:针对变电站通信过程中干扰检测效率不高的问题,提出一种改进的CUSUM算法检测方案。该方法基于统计学中的序贯概率比,利用非参数CUSUM算法来累积偏差,放大干扰引起的特征变化并对其进行判别。为了适应干扰攻击和信道状况的不确定性,加入滑动窗口与自适应阈值算法实现对干扰的实时检测。运用改进的CUSUM算法在时域对接收信号进行检测,分析累积图的变化过程,与N-sigma、Z-score 2种检测方式比较,仿真结果表明,所提方法的检测效果明显优于二者,其虚警率和漏警率分别为4.0%和5.3%,能灵敏地检测出干扰出现的时刻,有效提升了系统干扰检测效率。Aimed at the low efficiency of interference detection in substation communication,a detection scheme by improved CUSUM algorithm is proposed.Based on the sequential probability ratio in statistics,this method uses the nonparametric CUSUM algorithm to cumulate the deviation,amplify the feature changes caused by interference and distinguish them.In order to adapt to interference attacks and the uncertainty of channel conditions,sliding window and adaptive threshold algorithm are added to realize real-time interference detection.The improved CUSUM algorithm is used to detect the received signal in the time domain,analyze the change process of the cumulative graph,and compared with N-sigma and Z-score detection methods.The simulation results show that the detection effect of the proposed method is obviously better than the two,and its false alarm rate and missed detection rate are 4.0%and 5.3%respectively,which can sensitively detect the time when interference occurs,and effectively improve the system interference detection efficiency.

关 键 词:变电站 CUSUM算法 通信过程 干扰检测 

分 类 号:TN975[电子电信—信号与信息处理]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象