一种智能电表自动化检定流水线表位在线异常检测方法

邢宇; 鲍志威; 孙艳玲; 李红斌; 陈勉舟; 焦洋

邢宇,鲍志威,孙艳玲,李红斌,陈勉舟,焦洋.一种智能电表自动化检定流水线表位在线异常检测方法[J].电测与仪表,2020,57(14):106-112.
Xing Yu,Bao Zhiwei,Sun Yanling,Li Hongbin,Chen Mianzhou,Jiao Yang.Online Anomaly Detection Method for Meter Positions in Automatic Verification Assembly Line of Smart Meter[J].Electrical Measurement & Instrumentation,2020,57(14):106-112.

一种智能电表自动化检定流水线表位在线异常检测方法

Online Anomaly Detection Method for Meter Positions in Automatic Verification Assembly Line of Smart Meter

DOI：10.19753/j.issn1001-1390.2020.14.018

中文关键词: 智能电表自动化检定流水线检定数据表位在线异常检测局部异常因子

英文关键词:smart meter, automatic verification assembly line, verification data, meter position, online anomaly detection, local outlier factor

基金项目:

作者中文名	作者英文名	单位
邢宇	Xing Yu	国网山东省电力公司电力科学研究院
鲍志威	Bao Zhiwei	华中科技大学电气与电子工程学院
孙艳玲	Sun Yanling	国网山东省电力公司电力科学研究院
李红斌	Li Hongbin	华中科技大学电气与电子工程学院
陈勉舟	Chen Mianzhou	华中科技大学电气与电子工程学院
焦洋	Jiao Yang	华中科技大学电气与电子工程学院

摘要点击次数: 1313

中文摘要:

自动化检定流水线为智能电表的正常运行提供保障，然而在长期运行过程中，其自身可能发生性能退化甚至故障，特别是检定表位机械压接环节的形变或锈蚀，导致误差试验结果出现偏差，因此，运维工作是极其必要的。目前，检定表位的运维依赖于定期开展的人工故障检测，无法及时响应运维间隔中出现的异常工况，存在异常检定表位仍服务于入网检定工作的风险，因此，实现自动化检定流水线表位异常的在线检测、及时识别表位异常，具有重要意义。文章提出了一种智能电表自动化检定流水线表位在线异常检测方法，通过对表位检定数据分布进行特征提取，将表位异常状态转换为数据分布的异常；并借助局部异常因子算法量化分布的异常程度，标记产生异常分布的表位；应用文章提出的方法对山东省电力公司计量中心智能电表检定数据进行了分析，对比人工检查结果，验证了方法的有效性。

英文摘要:

Automatic verification assembly line provides guarantee for the normal operation of smart meters. However, in the long-term operation process, performance degradation or even failure may occur, especially the deformation or rust of the mechanical link of the meter positions, resulting in deviation of the error test results. Consequently, the maintenance of meter positions is extremely necessary. At present, the maintenance of meter positions depends on the manual detection carried out regularly, and it is unable to respond to the abnormal working conditions occurring in the maintenance interval in time, and the abnormal meter positions still serve the risk. Therefore, it is of great significance to implement the online detection of the abnormal meter positions in the assembly line and to identify the problems in time. This paper proposes a method for online detection of meter positions’ anomalies in automatic verification assembly line, extracts the characteristics of the verification data distribution of the meter positions, and converts the abnormal state of the meter positions into the abnormality of data distribution. Then, the local outlier factor algorithm is used to quantify the abnormal degree of distribution, and the meter positions with abnormal distribution will be marked. Finally, this paper analyzes the smart meter verification data of the Metrology Center of Shandong Electric Power Company, and the results show that this method is effective.

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