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。
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 zerosequence current of leakage and interfering signal according to historical data of a branch,so as to improve accuracy of line selection criterion.
出处
《工矿自动化》
北大核心
2015年第10期36-39,共4页
Journal Of Mine Automation
基金
中央高校基本科研业务费专项资金项目(00-800015G2)
