Monitoring near burner slag deposition with a hybrid neural network system

C K Tan; Steven Wilcox; J Ward; M Lewitt

doi:10.1088/0957-0233/14/7/332

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Monitoring near burner slag deposition with a hybrid neural network system

Journal article

Peer reviewed

Monitoring near burner slag deposition with a hybrid neural network system

C K Tan, Steven Wilcox, J Ward and M Lewitt

Measurement Science and Technology, Vol.14(7), pp.1137-1145

2003

DOI: https://doi.org/10.1088/0957-0233/14/7/332

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Abstract

Burner eyebrow

Coal-fired boiler

Neural networks

This paper is concerned with the development of a system to detect and monitor slag growth in the near burner region in a pulverized-fuel (pf) fired combustion rig. These slag deposits are commonly known as 'eyebrows' and can markedly affect the stability of the burner. The study thus involved a series of experiments with two different coals over a range of burner conditions using a 150 kW pf burner fitted with simulated eyebrows. These simulated eyebrows consisted of annular refractory inserts mounted immediately in front of the original burner quarl. Data obtained by monitoring the infra-red radiation and sound emitted by the flame were processed to yield time and frequency-domain features, which were then used to train and test a hybrid neural network. This hybrid 'intelligent' system was based on self organizing map and radial-basis-function neural networks. This system was able to classify different sized eyebrows with a success rate of at least 99.5%. Consequently, it is possible not only to detect the presence of an eyebrow by monitoring the flame, but also the network can provide an estimate of the size of the deposit, over a reasonably large range of conditions.

Details

Title: Monitoring near burner slag deposition with a hybrid neural network system
Authors: C K Tan (Author) - University of Glamorgan
Steven Wilcox (Author) - University of Glamorgan
J Ward (Author) - University of Glamorgan
M Lewitt (Author)
Publication details: Measurement Science and Technology, Vol.14(7), pp.1137-1145
Publisher: Institute of Physics Publishing Ltd.
Date published: 2003
DOI: 10.1088/0957-0233/14/7/332
ISSN: 0957-0233; 0957-0233
Organisation Unit: Office of the Deputy Vice-Chancellor (Academic); University of the Sunshine Coast, Queensland
Language: English
Record Identifier: 99513806702621
Output Type: Journal article

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Web Of Science research areas: Engineering, Multidisciplinary; Instruments & Instrumentation