东南大学学报（英文版）2005，Vol.21Issue(1)：44-47,4.
热力参数软仪表在电厂中的应用
Application of thermal parameter soft sensor in power plant
摘要
Abstract
In order to solve the problem of the invalidation of thermal parameters and optimal running,we present an efficient soft sensor approach based on sparse online Gaussian processes(GP),which is based on a combination of a Bayesian online algorithm together with a sequential construction of a relevant subsample of the data to specify the prediction of the GP model.By an appealing parameterization and projection techniques that use the reproducing kernel Hilbert space(RKHS) norm,recursions for the effective parameters and a sparse Gaussian approximation of the posterior process are obtained.The sparse representation of Gaussian processes makes the GP-based soft sensor practical in a large dataset and real-time application.And the proposed thermal parameter soft sensor is of importance for the economical running of the power plant.关键词
高斯过程/软仪表/稀疏逼近/在线学习/经济运行Key words
Gaussian process/soft sensor/sparse approximation/online learning/economical monitoring分类
能源科技引用本文复制引用
熊志化,朱峰,邵惠鹤..热力参数软仪表在电厂中的应用[J].东南大学学报（英文版）,2005,21(1):44-47,4.基金项目
The National High Technology Research and Development Program of China (863 Program)(No.2002AA412010). （863 Program）
