摘要
为利用长期积累的单一煤灰结渣指标数据直接预测煤灰结渣特性,以煤灰成分S iO2、A l2O3、Fe2O3、CaO、MgO、Na2O、K2O和TiO2作为输入变量,实际结渣程度作为输出变量,基于支持向量机建立了煤灰结渣特性诊断模型。通过对某热电厂锅炉煤灰样本的诊断,表明该诊断模型具有较高的评判准确率。
To accurately analyze coal ash slag-buildup characteristics,a model based on support vector machine（SVM） was built,in which there were eight input vectors,i.e.SiO2,Al2O3,Fe2O3,CaO,MgO,Na2O,K2O,and TiO2 content of the coal ash,and one output vector,i.e.the actual slagging degree of the coal ash.The model was proved effective and accurate through its application to diagnosis of coal ash sample from a thermal power plant.
出处
《华东电力》
北大核心
2009年第11期1925-1927,共3页
East China Electric Power
基金
国家重点研究发展计划(973计划)项目(2007CB206904)
关键词
煤灰
结渣特性
支持向量机
诊断模型
coal ash
slag-buildup characteristic
support vector machine（SVM）
diagnosis model
