DocumentCode :
3724276
Title :
Soft Sensor Modeling for Oxygen-Content in Flue Gasses in 1000MW Ultra-superficial Units
Author :
Shihe Chen;Zhang Xi;Weiwu Yan;Dandan Zhang
Author_Institution :
Guangdong Electr. Power Res. Inst., Guangzhou, China
fYear :
2015
Firstpage :
164
Lastpage :
167
Abstract :
Ultra-supercritical unit, which can implement clean coal combustion and improve energy efficiency, is an important trend of thermal power plants in China. Aiming to the measurement of oxygen-content in flue gasses in Ultra-supercritical unit in a power plant, this paper discusses a soft-sensing model method based on Gaussian process regression (GPR). Then GPR based soft sensor is applied to estimate the Oxygen-content in Flue Gasses in 1000MW Ultra-superficial Units. The experiment results show that the method of soft-sensing based on Gaussian process regression is not only easy to implement, but also has small predicted error and uncertainty.
Keywords :
"Ground penetrating radar","Gaussian processes","Power generation","Coal","Testing","Training data","Combustion"
Publisher :
ieee
Conference_Titel :
Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), 2015 International Conference on
Type :
conf
DOI :
10.1109/ICIICII.2015.124
Filename :
7373812
Link To Document :
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