基于主元回归的发电厂烟气含氧量软测量研究

Soft-sensing Study on Oxygen Content in Flue Gas of Power Plant Based On Principal Component Regression

为了有效测量炉膛烟气含氧量,采用主元回归建模的方法,对几个与烟气含氧量有关的过程变量进行统计分析,建立了烟气含氧量的预测模型,实现了对烟气含氧量的软测量。利用主元回归建模的方法可以降低对数据维数的要求,消除各个过程变量间的耦合性,简化模型,并能有效提高建模的计算效率。

To measure oxygen content in flue gas effectively,this paper applies the method of principal component regression.By analyzing several procedure variables which are involved with oxygen content,the paper forms a prediction model and realizes the measurement about oxygen content.The method of principal component regression can reduce the dimension of data requirements, avoid the coupling among each variable,make the model simpler and improve the efficiency of modeling.