化工学报2011，Vol.62Issue(8)：2248-2252,5.DOI:10.3969/j.issn.0438-1157.2011.08.028
一种基于多模型融合软测量建模方法
A multi-model fusion soft sensor modeling method
摘要
Abstract
As for low forecast accuracy of cobalt ion concentration by least square support vector machine (LS-SVM) method in the purification process of zinc hydrometallurgy, a multi-model fusion soft sensor modeling method based on combination LS-SVM with ARMA model was introduced in purification of zinc. Firstly the series of cobalt ion concentration was decomposed by wavelet transform, the decomposed sub-sequences were reconstructed by phase space reconstruction. Each sub-sequence was modeled by LS-SVM method in phase space, then the output of each model was integrated by wavelet reconstruction. Secondly correction was made for error of LS-SVM modeling output in ARMA model. Finally the output of two models were integrated, the integration value was the estimated value of cobalt ion concentration. The method was applied in prediction of cobalt ion concentration in the entrance of purification process of zinc hydrometallurgy. The results showed that this method had better generalization performance and high prediction accuracy than LS-SVM method, which showed good potential for application.关键词
小波变换/相空间重构/多模型融合/软测量/锌净化Key words
wavelet transform/ phase space reconstruction/ multi-model fusion/ soft sensor model/purification of zinc分类
信息技术与安全科学引用本文复制引用
唐志杰,唐朝晖,朱红求..一种基于多模型融合软测量建模方法[J].化工学报,2011,62(8):2248-2252,5.基金项目
国家高技术研究发展计划项目(2009AA042124) （2009AA042124）
国家自然科学基金重点项目(60634020). （60634020）
