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