摘要
为有效管理电能表故障,基于关联分析理论,引入模糊集与FP-Growth算法,构建一种新型故障数据分析模型,用以分析电能表属性与故障间关联关系,识别出潜在的家族性缺陷。利用某省级电力公司电能表故障数据对模型进行了验证。运行结果表明,该模型具有方法可行、结果准确、运算效率高等特点,能够对海量数据进行高效处理。
In order to identify the familial defects of electricity meters and deal with the faults effectively,this paper proposed a new model to analyze the fault of watt-hour meter and identify potential familial defects based on the theory of association analysis and FP-growth algorithm.The model is verified by using the data obtained from a certain provincial electric power company.The experimental results show that the model has the advantages such as feasibility,accuracy and efficiency,and can be used to deal with the massive data effectively.
作者
陈霄
季欣荣
王德玉
宋瑞鹏
CHEN Xiao;JI Xinrong;WANG Deyu;SONG Ruipeng(State Grid Jiangsu Electric Power Co.,Ltd.,Jiangsu Nanjing 210000,China;Electric Power Research Institute of State Grid Jiangsu Electric Power Co.,Ltd.,Jiangsu Nanjing 210008,China)
出处
《电器与能效管理技术》
2019年第11期14-19,23,共7页
Electrical & Energy Management Technology
基金
江苏省自然科学基金项目(BK20150823)
关键词
电能表
关联分析
全数据模型
故障分析
watt-hour meter
correlation analysis
full data model
failure analysis
