Title :
On-line identification of biomass fuels based on flame radical and application of Support Vector Machine techniques
Author :
Li, X.L. ; Li, Ning ; Lu, Guo-Quan ; Yan, Y.
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
In biomass fired power plants, a range of biomass fuels are used to generate electric power. It is vitally important to identify the type of biomass on-line in order to improve combustion efficiency, reduce emissions and ensure the boiler safety. Present research focuses on the on-line identification of biomass fuels using flame radical imaging and SVM (Support Vector Machine) techniques. The characteristic values of flame radicals, including OH*, CN*, CH* and C2*, are extracted and used to reconstruct the SVM for on-line fuel identification. Experimental results obtained on a laboratory-scale biomass-gas-fired combustion test rig demonstrate the effectiveness of the proposed method.
Keywords :
bioenergy conversion; flames; power engineering computing; renewable energy sources; support vector machines; SVM; biomass fired power plants; biomass fuels; biomass-gas-fired combustion test rig; boiler safety; combustion efficiency; emission reduction; flame radical imaging; online fuel identification; online identification; support vector machine; support vector machine techniques; biomass fuel; flame radical; identification; support vector machine;
Conference_Titel :
Renewable Power Generation Conference (RPG 2013), 2nd IET
Conference_Location :
Beijing
Electronic_ISBN :
978-1-84919-758-8
DOI :
10.1049/cp.2013.1737