Soft-sensing model of oxygen content based on data fusion

Author

Liu, Ji-zhen ; Zhao, Zheng ; Zeng, De-liang ; Chen, Yan-Qiao

Author_Institution

Autocontrol Dept., North China Electr. Power Univ., Baoding, China

Volume

7

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

3991

Abstract

The soft-sensing technique of oxygen content in flue gases based on data fusion is presented according to the high first cost of conventional oxygen content analyzers, their high maintenance expenses and low durability. Through the mechanism analysis and the statistical analysis of a number of data, soft-sensing models of oxygen content and air flow. etc. are set up. Based on multisensor data fusion, more reliable and accurate values of input data are obtained. At last, this soft-sensing model fit well with the practical oxygen content, which is illustrated by the simulations.

Keywords

chemical engineering computing; chemical sensors; chemical variables measurement; combustion; neural nets; oxygen; sensor fusion; statistical analysis; air flow; data fusion; flue gases; oxygen content analysis; soft-sensing technique; statistical analysis; Boilers; Combustion; Costs; Flue gases; Industrial control; Industrial economics; Maintenance; Oxygen; Power generation economics; Statistical analysis; Data fusion; Mechanism analysis; Oxygen content; Soft-sensing model; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527635

Filename

1527635