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Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement

Hossain, Md. Moinul (2019) Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement. Journal of Chinese Physics B, 28 (3). Article Number 34207. ISSN 1674-1056. (doi:10.1088/1674-1056/28/3/034207) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:72061)

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Abstract

It is essential to investigate the light field camera parameters for the accurate flame temperature measurement because the sampling characteristics of the flame radiation can be varied with the light field camera parameters. In this study, novel indices of the light field camera were proposed to investigate the directional and spatial sampling characteristics of the flame radiation. Effects of light field camera parameters such as focal length and magnification of the main lens, focal length and magnification of the microlens were investigated. It has been observed that the sampling characteristics of the flame are varied with the different parameters of the light field camera. The optimized parameters of the light field camera were then proposed for the flame radiation sampling. The larger sampling angle (23 times larger) is achieved by the optimized parameters compared to the commercial light field camera parameters. A non-negative least square (NNLS) algorithm was used to reconstruct the flame temperature. The reconstruction accuracy was also evaluated by the optimized parameters. The results suggested that the optimized parameters can provide higher reconstruction accuracy for axisymmetric and non-symmetric flame conditions in comparison to the commercial light field camera.

Item Type: Article
DOI/Identification number: 10.1088/1674-1056/28/3/034207
Uncontrolled keywords: Light field camera; Flame radiation sampling; Parameter optimization; Temperature reconstruction
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Moinul Hossain
Date Deposited: 29 Jan 2019 12:45 UTC
Last Modified: 04 Mar 2024 18:18 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/72061 (The current URI for this page, for reference purposes)

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