摘要
通过分析燃煤电厂烟气含氧量测量的现状。提出了基于最小二乘支持向量机的软测量方法,给出了相应的系统结构和算法,用现场实测数据计算取得了良好的效果。通过和神经网络方法的比较,仿真结果证明了该方法具有更好的性能指标。
The measuring methods of Oxygen-content in flue gases of Coal-fired power plant are analyzed.A soft-sensing scheme is presented,which is based on least squares support vector machines. Soft-sensing system structure and algorithm are given. The softsensor has been applied to in field, and good performance has been validated.Compared with RBF neural network, simulation result shows that the proposed method actually increases the accuracy of LS-SVM.
出处
《微计算机信息》
北大核心
2006年第10S期241-243,290,共4页
Control & Automation
基金
国家自然科学基金项目(资助号:50576022)
关键词
烟气含氧量
最小二乘支持向量机
软测量
神经网络
Oxygen-content in flue gases,Least squares support vector machines,Soft-sensing,neural network
