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文章摘要
基于局部异常点检测算法的电能表飞走异常智能分析
The intelligent analysis of the electric energy meter based on LOF(local outlier factor)
Received:October 27, 2015  Revised:April 05, 2016
DOI:
中文关键词: 智能电能表  用电信息采集系统  LOF  异常点
英文关键词: smart electric energy meter, power information acquisition system, LOF, Abnormal point
基金项目:
Author NameAffiliationE-mail
Li Yifei* State Grid Beijing Electric Power Research Institute,Beijing 13581714955@139.com 
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中文摘要:
      针对用电信息采集系统在计量设备在线监控业务应用的实际情况,本文介绍了一种基于LOF局部异常点检测算法的电能表飞走异常分析方法,该方法可以通过计算电能表示值异常因子,有效判断电能表示值异常属于偶然异常还是趋势性异常,在排除偶然数据的影响后,进行电能表飞走异常的二次判断。该方法可以有效提高该类异常判断的准确性,避免故障误判,提高了现场故障处理的工作效率。
英文摘要:
      Aiming at the actual situation of the on-line monitoring and controlling system of the electric information acquisition system, the paper introduces a method of detecting the anomaly of the electric energy meter based on the LOF outlier detection algorithm, which can be used to detect the occasional anomaly or the trend anomaly. This method can effectively improve the accuracy of this kind of anomaly judgment, avoid the fault of the fault, and improve the working efficiency of the fault treatment.
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