# On-line identification of biomass fuels based on flame radical imaging and application of radical basis function neural network techniques

Li, Xinli, Yan, Yong, Liu, Shi, Wu, Mengjiao, Lu, Gang (2015) On-line identification of biomass fuels based on flame radical imaging and application of radical basis function neural network techniques. IET Renewable Power Generation, 9 (4). pp. 323-330. ISSN 1752-1416. (doi:10.1049/iet-rpg.2013.0392) (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)

 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. (Contact us about this Publication) Official URLhttp://doi.org/10.1049/iet-rpg.2013.0392

## Abstract

In biomass fired power plants a range of biomass fuels are used to generate electric power. It is desirable to identify the type of biomass fuels on-line continuously in order to achieve an improved combustion efficiency, and reduced pollutant emissions. This paper presents the recent investigations into the on-line identification of biomass fuels based on the combination of flame radical imaging and radical basis function (RBF) neural network (NN) techniques. The characteristic values of flame radicals (OH*, CN*, CH* and C2*), including the intensity ratio, intensity contour, mean intensity, area and eccentricity, are computed to reconstruct two types of RBF NN, that is, accurate and probabilistic RBF networks. Experimental results obtained for three types of biomass fuels (flour, willow sawdust and palm kernel shell) firing on a laboratory-scale combustion test rig are presented to demonstrate the effectiveness of the proposed method.

Item Type: Article 10.1049/iet-rpg.2013.0392 T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation Faculties > Sciences > School of Engineering and Digital ArtsFaculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems Tina Thompson 07 May 2015 09:24 UTC 06 Feb 2020 04:12 UTC https://kar.kent.ac.uk/id/eprint/48286 (The current URI for this page, for reference purposes) https://orcid.org/0000-0002-9093-6448