摘要
采用传统方法对电网设备监控信息进行分类时,缺少对监控信息的预处理步骤,导致分类效果较差,为了解决该问题,提出了基于大数据的电网设备监控信息自动分类方法。分析电网设备监控信息数据采集结构,对信息数据进行预处理,并在大数据环境下,采取信息梳理的方式合理合并相关同类事项。设计信息梳理流程,将信息进行归档,以此构建信息熵数学模型,计算电网设备出现故障的几率,获取有效预警信息文档。依据信息自动分类流程,实现对电网设备监控信息的自动分类。通过实验对比结果可知,采用基于大数据方法分类效果最高可达到98%,说明该方法适应了电力大数据快速增长趋势,能够为设备监控信息分类提供有力支持。
When the traditional equipment is used to classify the monitoring information of power grid equipment,the pre-processing steps of monitoring information are lacking,resulting in poor classifica.tion effect.In order to solve this problem,an automatic classification method for monitoring information of power grid equipment based on big data is proposed.Analyze the data collection structure of the monitor.ing information of the power grid equipment,pre-process the information data,and reasonably merge relevant related matters in a big data environment.Design information combing process,archive informa.tion,construct information entropy mathematical model,calculate the probability of grid equipment failure,and obtain effective warning information document.According to the automatic classification process of information,automatic classification of monitoring information of power grid equipment is realized.The experimental comparison results show that the classification effect based on big data method can reach 98%,which indicates that the method adapts to the rapid growth trend of power big data and can provide strong support for equipment monitoring information classification.
作者
陆晓
刘翌
齐敬先
霍雪松
蒋宇
LU Xiao;LIU Yi;QI Jing-xian;HUO Xue-song;JIANG Yu(China National Network Jiangsu Electric Power Co.,Ltd.,Nanjing 210000,China;Nari GroupCorporation/State Grid Electric Power Reseach Institute,Nanjing 21000,China)
出处
《电子设计工程》
2019年第11期119-122,127,共5页
Electronic Design Engineering
基金
江苏省电网公司科技项目(J2017007)
关键词
大数据
电网设备
监控信息
自动分类
数据采集
预处理
big data
power grid equipment
monitoring information
automatic classification
data acquisition
pretreatment
