化工进展2019，Vol.38Issue(3)：1573-1578,6.DOI:10.16085/j.issn.1000-6613.2018-1190
电站锅炉省煤器受热面的积灰监测
Online monitoring heating surface pollution of a boiler economizer in coal-fired power plant
摘要
Abstract
To realize online monitoring heating surface pollution of an economizer in coal-fired power plant boiler, support vector machine (SVM) algorithm was used to predict the clean heat absorption of the economizer. At the same time, the gray wolf algorithm (GWO) and genetic algorithm was used for parameters optimization, and prediction accuracy in two models was compared. According to the cleaning heat absorption, the cleaning factor was calculated. The economizer's fouling was judged according to the change of cleaning factor. Take a 660 MW unit as an example, the data after short blow was taken as clean samples for training and validation. The results showed that GWO has higher prediction accuracy than genetic algorithm (GA), and the training time of GWO is shorter. Finally, this model was used to predict the clean heat absorption of an economizer before long blowing, then the clean factor curve was drawn.The fouling in an economizer heating surface can be performed well. Thus, a basis for an economizer fouling on-line monitoring is offered.关键词
电站燃煤锅炉/省煤器/积灰/支持向量机/灰狼算法/清洁因子Key words
coal-fired power plant boiler/economizer/fouling/support vector machine/grey wolf optimization algorithm/cleaning factor分类
能源科技引用本文复制引用
肖海平,陈裕辉,葛金林,王晓宁,席建林,刘利宁..电站锅炉省煤器受热面的积灰监测[J].化工进展,2019,38(3):1573-1578,6.基金项目
华能集团总部科技项目(HNK J18-H21) （HNK J18-H21）
国家科技支撑计划(2015BAA04B02) （2015BAA04B02）
