Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine

The gas turbine was one of the most important technological developments of the early 20th century, and it has had a significant impact on our lives. Although some researchers have worked on predicting the performance of three-shaft gas turbines, the effects of the deteriorated components on other p...

Descripción completa

Detalles Bibliográficos
Autores principales: Salilew, Waleligne Molla, Abdul Karim, Zainal Ambri, Lemma, Tamiru Alemu, Fentaye, Amare Desalegn, Kyprianidis, Konstantinos G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407329/
https://www.ncbi.nlm.nih.gov/pubmed/36010716
http://dx.doi.org/10.3390/e24081052
_version_ 1784774337765572608
author Salilew, Waleligne Molla
Abdul Karim, Zainal Ambri
Lemma, Tamiru Alemu
Fentaye, Amare Desalegn
Kyprianidis, Konstantinos G.
author_facet Salilew, Waleligne Molla
Abdul Karim, Zainal Ambri
Lemma, Tamiru Alemu
Fentaye, Amare Desalegn
Kyprianidis, Konstantinos G.
author_sort Salilew, Waleligne Molla
collection PubMed
description The gas turbine was one of the most important technological developments of the early 20th century, and it has had a significant impact on our lives. Although some researchers have worked on predicting the performance of three-shaft gas turbines, the effects of the deteriorated components on other primary components and of the physical faults on the component measurement parameters when considering the variable inlet guide valve scheduling and secondary air system for three-shaft gas turbine engines have remained unexplored. In this paper, design point and off-design performance models for a three-shaft gas turbine were developed and validated using the GasTurb 13 commercial software. Since the input data were limited, some engineering judgment and optimization processes were applied. Later, the developed models were validated using the engine manufacturer’s data. Right after the validation, using the component health parameters, the physical faults were implanted into the non-linear steady-state model to investigate the performance of the gas turbine during deterioration conditions. The effects of common faults, namely fouling and erosion in primary components of the case study engine, were simulated during full-load operation. The fault simulation results demonstrated that as the severity of the fault increases, the component performance parameters and measurement parameters deviated linearly from the clean state. Furthermore, the sensitivity of the measurement parameters to the fault location and type were discussed, and as a result they can be used to determine the location and kind of fault during the development of a diagnosis model.
format Online
Article
Text
id pubmed-9407329
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-94073292022-08-26 Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine Salilew, Waleligne Molla Abdul Karim, Zainal Ambri Lemma, Tamiru Alemu Fentaye, Amare Desalegn Kyprianidis, Konstantinos G. Entropy (Basel) Article The gas turbine was one of the most important technological developments of the early 20th century, and it has had a significant impact on our lives. Although some researchers have worked on predicting the performance of three-shaft gas turbines, the effects of the deteriorated components on other primary components and of the physical faults on the component measurement parameters when considering the variable inlet guide valve scheduling and secondary air system for three-shaft gas turbine engines have remained unexplored. In this paper, design point and off-design performance models for a three-shaft gas turbine were developed and validated using the GasTurb 13 commercial software. Since the input data were limited, some engineering judgment and optimization processes were applied. Later, the developed models were validated using the engine manufacturer’s data. Right after the validation, using the component health parameters, the physical faults were implanted into the non-linear steady-state model to investigate the performance of the gas turbine during deterioration conditions. The effects of common faults, namely fouling and erosion in primary components of the case study engine, were simulated during full-load operation. The fault simulation results demonstrated that as the severity of the fault increases, the component performance parameters and measurement parameters deviated linearly from the clean state. Furthermore, the sensitivity of the measurement parameters to the fault location and type were discussed, and as a result they can be used to determine the location and kind of fault during the development of a diagnosis model. MDPI 2022-07-31 /pmc/articles/PMC9407329/ /pubmed/36010716 http://dx.doi.org/10.3390/e24081052 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Salilew, Waleligne Molla
Abdul Karim, Zainal Ambri
Lemma, Tamiru Alemu
Fentaye, Amare Desalegn
Kyprianidis, Konstantinos G.
Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title_full Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title_fullStr Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title_full_unstemmed Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title_short Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine
title_sort predicting the performance deterioration of a three-shaft industrial gas turbine
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9407329/
https://www.ncbi.nlm.nih.gov/pubmed/36010716
http://dx.doi.org/10.3390/e24081052
work_keys_str_mv AT salilewwalelignemolla predictingtheperformancedeteriorationofathreeshaftindustrialgasturbine
AT abdulkarimzainalambri predictingtheperformancedeteriorationofathreeshaftindustrialgasturbine
AT lemmatamirualemu predictingtheperformancedeteriorationofathreeshaftindustrialgasturbine
AT fentayeamaredesalegn predictingtheperformancedeteriorationofathreeshaftindustrialgasturbine
AT kyprianidiskonstantinosg predictingtheperformancedeteriorationofathreeshaftindustrialgasturbine