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Flame stability detection method for co-firing of biomass fuels based on digital image processing

Ge, Hong, Xu, Weicheng, Yan, Yong, Lu, Gang (2019) Flame stability detection method for co-firing of biomass fuels based on digital image processing. Thermal Power Generation, . ISSN 1002-3364. (KAR id:89774)

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Abstract

Combustion of low-quality fuels or fuel blends will lead to flame instability, resulting in low combustion efficiency and high NOx emissions. Due to the inherent complexity of burner flames and the lack of an effective means for flame monitoring and characterization, it is difficult to evaluate the flame stability in a combustion process quantitatively. To solve this problem, a method based on digital image processing for co-firing biomass fuels is proposed in this paper to monitor various characteristic parameters of a burner flame and evaluate its stability. In this method, a general flame stability index with continuous values in the range of [0, 1] is defined, and by using a digital CCD camera, the flame image information is collected. After the collected image is analyzed, the characteristic parameters like the flame length/height, brightness, temperature, flicker frequency and others are extracted. Then, statistical analysis and data fusion are carried out for theses characteristic parameters, and the flame stability index is obtained. Thus, the quantitative detection and evaluation of flame stability is realized. Moreover, this method was verified on a laboratory-scale combustion test rig. The combustion behaviours of different biomass blends(corncob-wheat straw blend, willow-peanut shell blend and peanut shell-wheat straw blend) were compared. The results show that, the defined flame stability index could effectively characterize the flame combustion state.

Item Type: Article
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA165 Engineering instruments, meters etc. Industrial instrumentation
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Yong Yan
Date Deposited: 14 Aug 2021 15:34 UTC
Last Modified: 14 Aug 2021 15:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/89774 (The current URI for this page, for reference purposes)
Xu, Weicheng: https://orcid.org/0000-0002-6508-7261
Yan, Yong: https://orcid.org/0000-0001-7135-5456
Lu, Gang: https://orcid.org/0000-0002-9093-6448
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