电力系统自动化2017，Vol.41Issue(19)：147-151,163,6.DOI:10.7500/AEPS20170306017
基于Apriori算法的二次设备缺陷数据挖掘与分析方法
Apriori Algorithm Based Data Mining and Analysis Method for Secondary Device Defects
张延旭 1胡春潮 1黄曙 1冯善强 1林冠强2
作者信息
- 1. 广东电网有限责任公司电力科学研究院,广东省广州市510080
- 2. 广东电网有限责任公司惠州供电局,广东省惠州市516000
- 折叠
摘要
Abstract
To enhance the maintenance and management level of secondary devices in the power system,a data mining and analysing method for secondary device defects based on the Apriori algorithm is proposed.Firstly,the basic ideas of association rules and Apriori algorithm are analyzed.Then a secondary defect model based on association rules is proposed,in which several important properties of secondary equipment defects (including secondary equipment manufacturer,device type,causes of device defects,position of device defect and defect levels) are taken into account.Furthermore,by taking the defect data of automation equipment as examples,the defect data mining and analyzing method based on data mining results are presented.Analysis results show that the proposed method is able to search for the weaknesses of secondary devices and the causes of weaknesses,while enunciating the family defects of devices.关键词
二次设备/关联规则/数据挖掘/Apriori算法Key words
secondary device/association rule/data mining/Apriori algorithm引用本文复制引用
张延旭,胡春潮,黄曙,冯善强,林冠强..基于Apriori算法的二次设备缺陷数据挖掘与分析方法[J].电力系统自动化,2017,41(19):147-151,163,6.
