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

Xu, Lijun and Yan, Yong and Cornwell, Steve and Riley, Gerry (2004) On-Line Fuel Identification Using Digital Signal Processing and Soft-Computing Techniques. In: Imtc/O3: Proceedings of the 20th IEEE Instrumentation and Measurement Technology Conference, vols 1 And 2. IEEE, 1 . IEEE, 345 E 47TH ST, New York, NY 10017 USA, USA pp. 1114-1118. ISBN 0-7803-7705-2 . (The full text of this publication is not available from this repository)

The full text of this publication is not available from this repository. (Contact us about this Publication)
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: Conference or workshop item (Paper)
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 (see also: telecommunications)
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Yiqing Liang
Date Deposited: 05 Aug 2009 07:35
Last Modified: 02 May 2014 09:29
Resource URI: http://kar.kent.ac.uk/id/eprint/7606 (The current URI for this page, for reference purposes)
  • Depositors only (login required):