Title :
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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527635
