基于粗糙集理论的设备缺陷大数据分析

Big Data Analysis of Equipment Defects Based on Rough Set Theory

针对变电运维室近几年来积累的大量设备缺陷数据,采用粗糙集理论对缺陷数据按照不同属性进行分类,分析同一属性数据中所隐含的规律,从而帮助运维人员找出设备缺陷的真正原因,指导班组正确、彻底地处理设备缺陷,消除电网安全隐患.同时采用本文的数据分析方法,对熔丝熔断缺陷等多个专项进行了成功地分析和总结,有效提高了缺陷处理的准确性,减少了非计划性停电的次数.

In this paper,according to the large amount of equipment defect data,which accumulated in the substation operation department in recent years,the rough set theory is used to classify the defect data according to the different attributes and analyze the hidden regulations in the same attribute data,in order to help the operation and maintenance personnel to find out the real cause of the equipment defect,and guide teams correctly and thoroughly deals with the equipment defects and eliminate the hidden danger of power grid security.Through the method of data analysis in this paper,many special items,such as fuse fusing defects,are successfully analyzed and summarized,which effectively improving the accuracy of the defect treatment and reducing the number of unplanned power outage effectively.