基于大数据挖掘的发电组温升预警方法研究  

Research on Early Warning Method of Generator Unit Temperature Rise Based on Large Data Mining

作　　者：张秋霞 韩彦敏 宋子涛 任党培 周志荣 ZHANG Qiuxia;HAN Yanmin;SONG Zitao;REN Dangpei;ZHOU Zhirong(State Power Investment Corporation Research Institute, Co. Ltd.,Beijing 102209;DHC Software Co. Ltd., Beijing 100190)

机构地区：[1]国家电投集团科学技术研究院有限公司,北京102209 [2]东华软件股份公司,北京100190

出　　处：《微型电脑应用》2020年第3期91-94,共4页Microcomputer Applications

摘　　要：传统方法所测得的残差无法作为判断发电组温升故障的依据,为解决这一问题,提出基于大数据挖掘的发电组温升故障预警方法研究。首先应用大数据挖掘技术收集数据,分析影响发电组温度的因素,依据发电组温度的因素与发电组温升故障预警基本原理,构建发电组温升故障预警逻辑判断结构;最后考虑到传统方法存在缺陷,运用大数据挖掘技术已有算法建立模型,实现预警,由此,完成基于大数据挖掘的发电组温升故障预警方法的设计。The residual measured by the traditional method cannot be used as the basis for judging the temperature rise fault of the power generation group.In order to solve this problem,a fault early warning method for the temperature rise of the power generation group based on big data mining is proposed.Firstly,big data mining technology is used to collect data,and the factors affecting the temperature of power generation group are analyzed.On this basis,according to the basic principle of temperature rise fault early warning of power generation group,the logic judgment structure of temperature rise fault early warning of power generation group is constructed.Finally,considering the defects of the traditional method,the existing algorithm of big data mining technology is used to establish the model and realize the early warning.Therefore,the design of temperature rise fault early warning method based on big data mining is completed.

关 键 词：大数据挖掘技术 故障预警 机组功率 环境温度 额定风速 

分 类 号：TM31[电气工程—电机]