首页 | 本学科首页   官方微博 | 高级检索  
     

基于集成模型的焦炉火道温度软测量技术研究与应用
引用本文:曹卫华,侯少云,吴敏.基于集成模型的焦炉火道温度软测量技术研究与应用[J].计算机测量与控制,2006,14(2):149-151.
作者姓名:曹卫华  侯少云  吴敏
作者单位:中南大学信息科学与工程学院,湖南,长沙,410083
基金项目:国家重点基础研究发展计划(973计划);高等学校优秀青年教师教学科研奖励计划
摘    要:在分析焦炉火道温度特性的基础上,提出了一种基于线性回归和神经网络模型的火道温度软测量集成模型;分析生产工艺得到典型蓄热室的选取原则,从典型蓄热室获得蓄顶温度,建立一元和二元线性回归模型反映蓄顶温度和火道温度的线性关系;建立神经网络模型拟和蓄顶温度和火道温度的非线性关系;最后利用误差最小法将线性回归模型和神经网络模型集成,提高软测量精度;模型实际运行效果验证了所建模型的有效性。

关 键 词:焦炉  软测量  神经网络  模型集成
文章编号:1671-4598(2006)02-0149-03
收稿时间:2005-06-15
修稿时间:2005-07-28

Research and Implementation of Coke Oven Flue Temperature Measurement via Soft-sensing Based on Integrated Models
Cao Weihua,Hou Shaoyun,Wu Min.Research and Implementation of Coke Oven Flue Temperature Measurement via Soft-sensing Based on Integrated Models[J].Computer Measurement & Control,2006,14(2):149-151.
Authors:Cao Weihua  Hou Shaoyun  Wu Min
Affiliation:School of Information Science and Engineering, Central South University, Changsha 410083, China
Abstract:An integrated model combining linear regress and neural network based on the features of coke oven flue temperature are proposed. Rules of selecting typical regenerators are put forward by analyzing features of process. Linear regression models are built to map the linear relationship between flue temperature and top of regenerator temperature; neural network models are built to map the nonlinear relationship. At last, least error method is employed to integrate the output of linear regression and neural network models. The run results of the models validate the method.
Keywords:coke oven  soft-sensing  neural network  integration of models
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号