Krabicka, Jan, Lu, Gang, Yan, Yong (2011) Profiling and Characterization of Flame Radicals by Combining Spectroscopic Imaging and Neural Network Techniques. IEEE Transactions on Instrumentation and Measurement, 60 (5). pp. 1854-1860. ISSN 0018-9456. (doi:10.1109/TIM.2010.2102411) (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:28009)
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/10.1109/TIM.2010.2102411 |
Abstract
This paper presents the development of an instrumentation
system for visualizing and characterizing free radicals in combustion flames. The system combines optical splitting, filtering,intensified imaging and image processing techniques for simultaneous and continuous monitoring of specific flame radicals (OH?, CN?, CH?, and C?2). Computing algorithms are developedto analyze the images and quantify the radiative characteristics of the radicals. Experimental results are obtained from a gas-fired
combustion rig to demonstrate the effectiveness of the system. The information obtained by the system is used to establish relationships between radical characteristics and air-to-fuel ratios of combustion gases, helping to obtain an in-depth understanding of burn characteristics.
Item Type: | Article |
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DOI/Identification number: | 10.1109/TIM.2010.2102411 |
Uncontrolled keywords: | Terms—Electron-multiplying charge-coupled device (EMCCD), flame, flame radicals, image processing, neural networks, principal component analysis (PCA) |
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: | J. Harries |
Date Deposited: | 14 Jul 2011 11:57 UTC |
Last Modified: | 16 Nov 2021 10:06 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/28009 (The current URI for this page, for reference purposes) |
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