基于SVR的燃煤机组NO_X含量的软测量模型  

Soft Sensor Model Based on SVR for the Measurement of NO_X Concentration of Coal-fired Unit

作　　者：李雅晶 辛妍丽 Li Yajing;Xin Yanli(School of Electric Power Engineering,South China University of Technology,Guangzhou 510640,China)

机构地区：[1]华南理工大学电力学院,广州510640

出　　处：《计算机测量与控制》2020年第8期62-66,共5页Computer Measurement &Control

基　　金：中央高校基本科研业务费专项资金(x2dlD2181850)。

摘　　要：作为火电厂燃煤脱硝工作的基础,选择性催化还原(SCR)脱硝反应器入口氮氧化物(NO_X)含量的测量至关重要;针对难以准确现场实时测量NO_X含量的问题,提出了基于回归型支持向量机(SVR)的软测量模型;首先对SCR反应器生成NO_X的过程进行机理分析,并结合相关性分析、主成分分析等数据处理方法选取辅助变量,然后基于回归型支持向量机算法建立模型,最后运用BP神经网络对模型进行检验,解决了SCR反应器入口NO_X的含量的难以准确预测问题;为SCR反应器入口NO_X含量的实时、准确测量打下基础。As a basis for denitration of coal-fired power plant,the measurement of nitrogen oxide(NO_X)content at the inlet of the Selective Catalytic Reduction(SCR)reactor is critical.In order to solve the problem that the NO_Xcontent cannot be accurately measured in real time,a soft sensing model based on regression support vector machine(SVR)is proposed.Firstly,the process of generating NO_Xat the inlet of SCR reactor is analyzed.Then auxiliary variables are selected by correlation analysis and principal component analysis,and the mathematics model based on support vector machine for regression algorithm is built.Finally,the model is tested by the method of BP artificial neural network.The proposed model lays the foundation for the real-time and accurate measurement of the NO_Xconcentration at the inlet of the SCR reactor.

关 键 词：NO_X含量 主成分分析 回归型支持向量机 BP神经网络 软测量 

分 类 号：TM62[电气工程—电力系统及自动化] TP274[自动化与计算机技术—检测技术与自动化装置]