基于支持向量机回归的火电厂烟气含氧量软测量

基金项目: 河北省发电过程仿真与优化工程技术研究中心资助项目．

详细信息

Soft-sensor for Oxygen Content in Flue Gas of Coal-fired Power Plant Based on SVR

School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China

摘要: 针对电厂中常用的氧化锆氧量传感器存在的投资大、寿命短、测量误差较大等问题，采用支持向量机回归方法对电厂分散控制系统采集到的数据进行处理，用核函数k（x_k；x_l）代替非线性问题中的内积运算，实现了由低维空间到高维空间的映射，从而使低维输入空间的非线性回归问题转化为高维特征空间的线性回归问题．给出了辅助变量、核函数、各种参数的选择方法．仿真实验验证了所提方法的可行性．
- 软测量 /
- 辅助变量 /
- 核函数 /
- 支持向量机回归（SVR）
Abstract: For the problems of great investment, short service life, big measurement errors, etc. in the zirconia sensors for the power plant, the support vector regression algorithm is applied to dealing with the data collected in the distributed control systems of power plant. Kernel function k(x_k;x_l) is used to realize mapping from low dimension to high dimension instead of the inner product process in the nonlinear problems. So the low dimension nonlinear regression problem is transformed into the high dimension linear regression problem. The selection methods of auxiliary variables, kernel functions, kinds of parameters are given. The feasibility of this method is verified by a simulation experiment.
- soft-sensor /
- auxiliary variable /
- kernel function /
- support vector regression (SVR)