摘要
随着计算机应用技术和现代电子技术的飞速发展,电力系统智能化程度越来越高。目前在线测温系统中储存了大量的数据,对于大数据的处理与分析,以及各种应用的挖掘,可以在现有的系统基础上得到极大的经济效益。本应用方案采用对设备历史温度数据进行曲线拟合,然后通过曲线相似度算法,对同类设备同时间段的温度数据趋势进行处理分析,从而智能判断该温度趋势是否正常。
With the rapid development of computer application technology and modern electronic technology, the intelligence of Power System is increasing. At present, a large amount of data is stored in the online temperature measurement system. For the processing and analysis of big data and the mining of various applications, great economic benefits can be obtained on the basis of the existing system. In this application scheme, the historical temperature data of the equipment is fitted by curve, and then the temperature data trend of the same kind of equipment in the same time period is processed and analyzed by curve similarity algorithm, so as to intelligence to determine whether the temperature trend is normal.
作者
何志甘
范彦琨
陈光焰
陈红强
朱光南
He Zhigan;Fan Yankun;Chen Guangyan;Chen Hongqiang;Zhu Guangnan(Maintenance Company,Fujian Electric Power Co.,Ltd,Fuzhou 350014;Zhejiang Dali Technology Co.,Ltd.,Hangzhou 310053)
出处
《仪器仪表标准化与计量》
2019年第5期46-48,共3页
Instrument Standardization & Metrology
关键词
大数据分析
曲线拟合
曲线相似度
温度趋势
故障预警
智能变电站
Big Data Analysis
Curve Fitting
Curve Similarity
Temperature Trend
Fault Early Warning
Intelligent Substation
