基于Apriori算法的电力系统二次设备缺陷数据挖掘与分析研究

Data mining and analysis of two equipment defects based on Apriori algorithm

为了能够使电力系统二次设备运行维护及管理控制水平得到提高,基于电力系统二次设备缺陷数据提出了基于Apriori算法的电力系统二次设备缺陷数据挖掘及分析方法。首先,对关联规则和Apriori算法的思路进行了全面的分析,之后创建以关联规则为基础的电力系统二次设备缺陷模型,通过模型思考二次设备缺陷的主要属性,包括二次设备类型、生产厂家及缺陷原因、部位等。最后,将自动化设备缺陷数据作为例子,分析基于Apriori算法的电力系统二次设备缺陷数据挖掘及分析方法。通过分析结果表示,所提出的方法能够满足二次设备缺陷数据挖掘及分析需求,并且寻找导致数据缺陷的原因,还能够对设备家族性缺陷进行分析。

In order to improve the operation and maintenance of the two equipment of the power system and improve the management and control level,the method of data mining and analysis of two equipment defects of power system based on the Apriori algorithm is proposed based on the two equipment defect data.First,a comprehensive analysis of the association rules and the thinking of the Apriori algorithm is carried out.After that,the two equipment defect model of power system based on the association rules is created,and the main attributes of the two equipment defects,including the two equipment type,the manufacturer and the defect cause and the location,are thought through the model.Finally,taking the defect data of automation equipment as an example,we analyze the two equipment defect data mining and analysis method based on Apriori algorithm.The analysis results show that the proposed method can meet the data mining and analysis requirements of two equipment defects,and find the causes of data defects,and can also analyze the family defects of the equipment.