<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Polish Maritime Research

This work is licensed under the Creative Commons Attribution 4.0 International License.

Very often, the operation of diagnostic systems is related to the evaluation of process functionality, where the diagnostics is carried out using reference...

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

Online veröffentlicht: 21. Dez. 2022

Seitenbereich: 123 - 131

DOI: https://doi.org/10.2478/pomr-2022-0050

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

© 2022 Tacjana Niksa-Rynkiewicz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Online veröffentlicht: 21. Dez. 2022

Seitenbereich: 123 - 131

DOI: https://doi.org/10.2478/pomr-2022-0050

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

© 2022 Tacjana Niksa-Rynkiewicz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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