Skip to main content
Kent Academic Repository

Profiling and Characterization of Flame Radicals by Combining Spectroscopic Imaging and Neural Network Techniques

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
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: 05 Nov 2024 10:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/28009 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.