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A novel method for the performance control of a gas transmission compressor.

Pearson, W N, Armitage, Alistair and Henderson, Douglas (2002) A novel method for the performance control of a gas transmission compressor. In: ASME TURBO EXPO 2002: Controls, Diagnostics and Instrumentation, Cycle Innovations, Marine, Oil and Gas Applications, 3rd-6th June 2002, Amsterdam, Netherlands.

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Abstract/Description

This paper presents the application of feed forward neural networks to the performance control of a gas transmission compressor. It is estimated that a global saving in compressor fuel gas of 1% could prevent the production of 6 million tonnes of CO2, per year, [1]. Results of compressor model testing suggest that compressor speed can be estimated to within ± 2.5%. The neural network property of function approximation is used to predict compressor speed for given process constraints and instrument input sets. The effects of training set size, instrument noise, reduced input sets and extrapolation from the training domain, are quantified. Various neural network architectures and training schema were examined. The embedding of a neural network into an expert system is also discussed.

Item Type: Conference or Workshop Item (Paper)
ISBN: 0791836010 CD of Proceedings
Additional Information: In: ASME TURBO EXPO 2002: Controls, Diagnostics and Instrumentation, Cycle Innovations, Marine, Oil and Gas Applications. American Society of Mechanical Engineers, International Gas Turbine Institute, Turbo Expo (Publication) IGTI, v 2 B, 2002, p 1173-1183
Uncontrolled Keywords: Compressors; Control systems; Carbon dioxide; Emission control; Approximation theory; Neural networks; Computer architecture; Uncontrolled terms: Performance control - Gas transmission compressor
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 006 Special Computer Methods
600 Technology > 620 Engineering > 621 Electronic & mechanical engineering
Library of Congress Subjects: T Technology > TJ Mechanical engineering and machinery
Q Science > QA Mathematics > QA76 Computer software
Item ID: 1808
Depositing User: RAE Import
Date Deposited: 06 Jun 2008 17:02
Last Modified: 07 Jul 2010 10:16
URI: http://researchrepository.napier.ac.uk/id/eprint/1808

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