基于大数据挖掘技术的工业锅炉性能优化升级研究  

Optimization and Upgrading of Industrial Boiler Performance Based on Big Data Mining Technology

作　　者：刘彩利[1] LIU Caili(Xi'an International University,Xi'an 710077,China)

机构地区：[1]西安外事学院,陕西西安710077

出　　处：《工业加热》2020年第10期37-39,47,共4页Industrial Heating

基　　金：陕西省科技厅重点研发项目_社会发展项目(2018SF-333)。

摘　　要：以600 MW燃煤发电机组为基本对象,向其中引入大数据挖掘技术,在其支持下探寻影响锅炉效率的典型因素,确定与各项参数相适应的最佳设定值。经研究得知,实行与大数据特性相符的计算方法,可获得适用于锅炉运行特性的目标值,以达到提升锅炉工作效率、节能减排的效果。Take 600MW coal-fired power generation unit as the basic object,the technology of big data mining was introduced into it,and the typical factors affecting boiler efficiency were studied with its support to determine the optimal set value suitable for various parameters.Through the study,it is known that the calculation method consistent with the characteristics of big data can obtain the target value applicable to the operation characteristics of the boiler,so as to improve the boiler work efficiency,energy saving and emission reduction effect.

关 键 词：大数据挖掘 锅炉性能 优化研究 

分 类 号：TK229.6[动力工程及工程热物理—动力机械及工程]