基于数据挖掘的方向保护选线判据的改进研究

李鹏举, 蒋小平, 郭婧宇, 黄超杰, 史玄, 李佳

李鹏举,蒋小平,郭婧宇,等.基于数据挖掘的方向保护选线判据的改进研究[J].工矿自动化,2015,41(10):36-39.. DOI: 10.13272/j.issn.1671-251x.2015.10.010
引用本文: 李鹏举,蒋小平,郭婧宇,等.基于数据挖掘的方向保护选线判据的改进研究[J].工矿自动化,2015,41(10):36-39.. DOI: 10.13272/j.issn.1671-251x.2015.10.010
LI Pengju, JIANG Xiaoping, GUO Jingyu, HUANG Chaojie, SHI Xuan, LI Jia. Improvement research of line selection criterion of direction protection based on data mining[J]. Journal of Mine Automation, 2015, 41(10): 36-39. DOI: 10.13272/j.issn.1671-251x.2015.10.010
Citation: LI Pengju, JIANG Xiaoping, GUO Jingyu, HUANG Chaojie, SHI Xuan, LI Jia. Improvement research of line selection criterion of direction protection based on data mining[J]. Journal of Mine Automation, 2015, 41(10): 36-39. DOI: 10.13272/j.issn.1671-251x.2015.10.010

基于数据挖掘的方向保护选线判据的改进研究

基金项目: 

中央高校基本科研业务费专项资金项目(00-800015G2)

详细信息
  • 中图分类号: TD611

Improvement research of line selection criterion of direction protection based on data mining

  • 摘要: 针对传统选线判据不能准确识别干扰信号、可能导致频繁误跳闸的问题,对传统选线方法进行了改进,即利用数据挖掘中的K-means算法进行聚类分析,根据某一支路的历史数据辨别漏电真零序电流和干扰信号,提高了选线判据的准确性。
    Abstract: In view of the problem that traditional line selection criterion can not accurately identify interfering signal and may cause frequent mistrip, improvement was carried out to traditional line selection method, namely using K-means algorithm of data mining for clustering analysis, and identifying true zero-sequence current of leakage and interfering signal according to historical data of a branch, so as to improve accuracy of line selection criterion.
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出版历程
  • 刊出日期:  2015-10-09

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