一种适用于配电自动化终端的遥测采样异常数据甄别方法  

A Method for Distinguishing Abnormal Data in Telemetry Sampling Suitable for Distribution Automation Terminals

作　　者：张斌[1] 张文波 ZHANG Bin;ZHANG Wenbo(Jicheng Electronics Co.,Ltd.,Jinan 250100;Nanjing Vocation University of Industry Technology,Nanjing 210023)

机构地区：[1]积成电子股份有限公司,山东济南250100 [2]南京工业职业技术大学,江苏南京210023

出　　处：《电力安全技术》2023年第10期60-63,共4页Electric Safety Technology

摘　　要：正确甄别遥测采集数据中的异常数据,是提高配电自动化终端切除短路故障可靠性的关键所在。在分析了遥测采集故障数据、正常数据、异常数据基本特性的基础上,提出了一种甄别异常数据的方法。该方法首先对遥测采集的同一周波原始数据进行内部分组,通过计算各相邻组间的相似性系数,利用含有异常数据时各相邻组间相似性系数存在的明显离散性,以此为判据实现对异常数据的甄别,从而提高配电自动化终端切除短路故障的可靠性。Correctly distinguishing abnormal data in the telemetry data collections is the key to improve the reliability of power distribution automation terminals in removing short circuit faults.On the basis of analyzing the basic characteristics of telemetry collected fault data,normal data,and abnormal data,a method for distinguishing abnormal data is proposed.It is to classify the original data of the same cycle collected by telemetry into several groups,calculate the similarity coefficient between adjacent groups,and uses the obvious dispersion of the similarity coefficient between adjacent groups when there is abnormal data,which is regarded as a criterion to identify abnormal data so as to improve the reliability of the distribution automation terminal to remove short circuit faults.

关 键 词：配电 遥测 异常数据 数据甄别 

分 类 号：TM764[电气工程—电力系统及自动化]