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Monitoring the Gas Turbine Start-Up Phase on a Platform Using a Hierarchical Model Based on Multi-Layer Perceptron Networks

Abstract

Very often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference models prepared on the basis of the process description in the nominal state. The main goal of the work is to develop a hierarchical gas turbine reference model for the estimation of start-up parameters based on multi-layer perceptron neural networks. A functional decomposition of the gas turbine start-up process was proposed, enabling a modular analysis of selected parameters of the process. Real data sets obtained from observations of the turbo-generator set located on a North Sea platform were used.

Keywords:

industrial gas turbine, start-up monitoring, artificial neural network, hierarchical system

Details

Issue
Vol. 29 No. 4 (2022)
Section
Latest Articles
Published
19-01-2023
DOI:
https://doi.org/10.2478/pomr-2022-0050
Licencja:
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Open Access License

This journal provides immediate open access to its content under the Creative Commons BY 4.0 license. Authors who publish with this journal retain all copyrights and agree to the terms of the CC BY 4.0 license.

 

Authors

  • Tacjana Niksa-Rynkiewicz

    Gdansk University of Technology, Poland
  • Anna Witkowska

    Gdansk University of Technology, Poland
  • Jerzy Głuch

    Gdansk University of Technology, Poland
  • Marcin Adamowicz

    Poland

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