Li, Xinli and Li, Ning and Lu, Gang and Yan, Yong (2013) On-line identification of biomass fuels based on flame radical and application of support vector machine techniques. In: 2nd IET Renewable Power Generation Conference (RPG 2013). IET. ISBN 978-1-84919-758-8. (doi:10.1049/cp.2013.1737) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:37104)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1049/cp.2013.1737 |
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.
Item Type: | Book section |
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DOI/Identification number: | 10.1049/cp.2013.1737 |
Uncontrolled keywords: | Biomass fuel; Flame radical; Identification; Support Vector Machine |
Subjects: | T Technology |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Tina Thompson |
Date Deposited: | 02 Dec 2013 14:37 UTC |
Last Modified: | 05 Nov 2024 10:21 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/37104 (The current URI for this page, for reference purposes) |
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