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On-Line Fuel Identification Using Digital Signal Processing and Soft-Computing Techniques

Xu, Lijun, Yan, Yong, Cornwell, Steve, Riley, Gerry (2004) On-Line Fuel Identification Using Digital Signal Processing and Soft-Computing Techniques. IEEE Transactions on Instrumentation and Measurement, 53 (4). pp. 1114-1118. ISSN 0018-9456. (doi:10.1109/TIM.2004.830573) (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:7606)

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.2004.830573

Abstract

This paper presents a novel approach for on-line fuel identification using digital signal processing and soft-computing techniques. Aflame detector containing three photodiodes is used to derive multiple signals covering a wide spectrum of the flame from infrared to ultraviolet through visible band Advanced digital signal processing and soft-computing techniques are deployed to identify the dynamic 'finger-prints' of the flame both in the time and frequency domains and ultimately the type of fuel being burnt. A series of experiments was carried out using a 0.5MW(th) combustion test facility operated by Innogy plc, UK. The results obtained demonstrate that this approach can be used to identify the type of fuel being burnt under steady combustion conditions.

Item Type: Article
DOI/Identification number: 10.1109/TIM.2004.830573
Uncontrolled keywords: Combustion, digital signal processing (DSP, flame detector, fuel identification, fuzzy logic, soft-computing
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Yiqing Liang
Date Deposited: 05 Aug 2009 07:35 UTC
Last Modified: 16 Nov 2021 09:45 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/7606 (The current URI for this page, for reference purposes)

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