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Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization
This paper aims to thoroughly investigate the potential of ion current measurements in the context of combustion process monitoring in gas turbines. The study is targeted at characterizing the dynamic behavior of a typical ion-current measurement system based on a spark-plug. Starting from the preli...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541023/ https://www.ncbi.nlm.nih.gov/pubmed/34696157 http://dx.doi.org/10.3390/s21206944 |
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author | Addabbo, Tommaso Fort, Ada Landi, Elia Mugnaini, Marco Parri, Lorenzo Vignoli, Valerio Zucca, Alessandro Romano, Christian |
author_facet | Addabbo, Tommaso Fort, Ada Landi, Elia Mugnaini, Marco Parri, Lorenzo Vignoli, Valerio Zucca, Alessandro Romano, Christian |
author_sort | Addabbo, Tommaso |
collection | PubMed |
description | This paper aims to thoroughly investigate the potential of ion current measurements in the context of combustion process monitoring in gas turbines. The study is targeted at characterizing the dynamic behavior of a typical ion-current measurement system based on a spark-plug. Starting from the preliminary study published in a previous work, the authors propose a refined model of the electrode (spark plug), based on the Langmuir probe theory, that incorporates the physical surface effects and proposes an optimized design of the conditioning electronics, which exploits a low frequency AC square wave biasing of the electrodes and allows for compensating some relevant parasitic effects. The authors present experimental results obtained in the laboratory, which allow for the evaluation of the validity of the model and the interpreting of the characteristics of the measurement signal. Finally, measurements carried out in the field on an industrial combustor are presented. The results confirm that the charged chemical species density sensed by the proposed measurement system and related to the mean value of the output signal is an indicator of the ‘average’ combustion process conditions in terms e.g., of air/fuel ratio, whereas the high frequency spectral component of the measured signal can give information related to the turbulent regime and to the presence of pressure pulsations. Results obtained with a prototype system demonstrated an achievable resolution of about 5 Pa on the estimated amplitude, even under small biasing voltage (22.5 V) and an estimated bandwidth of 10 kHz. |
format | Online Article Text |
id | pubmed-8541023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85410232021-10-24 Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization Addabbo, Tommaso Fort, Ada Landi, Elia Mugnaini, Marco Parri, Lorenzo Vignoli, Valerio Zucca, Alessandro Romano, Christian Sensors (Basel) Article This paper aims to thoroughly investigate the potential of ion current measurements in the context of combustion process monitoring in gas turbines. The study is targeted at characterizing the dynamic behavior of a typical ion-current measurement system based on a spark-plug. Starting from the preliminary study published in a previous work, the authors propose a refined model of the electrode (spark plug), based on the Langmuir probe theory, that incorporates the physical surface effects and proposes an optimized design of the conditioning electronics, which exploits a low frequency AC square wave biasing of the electrodes and allows for compensating some relevant parasitic effects. The authors present experimental results obtained in the laboratory, which allow for the evaluation of the validity of the model and the interpreting of the characteristics of the measurement signal. Finally, measurements carried out in the field on an industrial combustor are presented. The results confirm that the charged chemical species density sensed by the proposed measurement system and related to the mean value of the output signal is an indicator of the ‘average’ combustion process conditions in terms e.g., of air/fuel ratio, whereas the high frequency spectral component of the measured signal can give information related to the turbulent regime and to the presence of pressure pulsations. Results obtained with a prototype system demonstrated an achievable resolution of about 5 Pa on the estimated amplitude, even under small biasing voltage (22.5 V) and an estimated bandwidth of 10 kHz. MDPI 2021-10-19 /pmc/articles/PMC8541023/ /pubmed/34696157 http://dx.doi.org/10.3390/s21206944 Text en © 2021 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 Addabbo, Tommaso Fort, Ada Landi, Elia Mugnaini, Marco Parri, Lorenzo Vignoli, Valerio Zucca, Alessandro Romano, Christian Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title | Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title_full | Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title_fullStr | Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title_full_unstemmed | Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title_short | Ion Current Sensor for Gas Turbine Condition Dynamical Monitoring: Modeling and Characterization |
title_sort | ion current sensor for gas turbine condition dynamical monitoring: modeling and characterization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541023/ https://www.ncbi.nlm.nih.gov/pubmed/34696157 http://dx.doi.org/10.3390/s21206944 |
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