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Marine Icing Sensor with Phase Discrimination

In this paper, a novel approach is presented to the measurement of marine icing phenomena under the presence of a two-phase condition. We have developed a sensor consisting of an electrostatic array and a signal processing based on a decision tree method. A three-element electrostatic array is emplo...

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Autores principales: Elzaidi, Abdulrazak, Masek, Vlastimil, Bruneau, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830499/
https://www.ncbi.nlm.nih.gov/pubmed/33477317
http://dx.doi.org/10.3390/s21020612
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author Elzaidi, Abdulrazak
Masek, Vlastimil
Bruneau, Stephen
author_facet Elzaidi, Abdulrazak
Masek, Vlastimil
Bruneau, Stephen
author_sort Elzaidi, Abdulrazak
collection PubMed
description In this paper, a novel approach is presented to the measurement of marine icing phenomena under the presence of a two-phase condition. We have developed a sensor consisting of an electrostatic array and a signal processing based on a decision tree method. A three-element electrostatic array is employed to derive signals having linearly decoupled characteristics from which two key parameters, ice and water accretion layer dimension, can be determined for the purpose of environmental monitoring. The quantified characteristics revealed a correlation with the ice layer thickness in spite of the strong influence from the top water phase layer. The decision tree model established a relationship between the signal characteristics and the two accretion thickness parameters of water and ice layer. Through experimental verification, it has been observed that our sensor array in combination with the decision tree model based signal processing provides a simple practical solution to the challenging field of a two phase composition measurement such as in the marine icing considered in this study.
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spelling pubmed-78304992021-01-26 Marine Icing Sensor with Phase Discrimination Elzaidi, Abdulrazak Masek, Vlastimil Bruneau, Stephen Sensors (Basel) Communication In this paper, a novel approach is presented to the measurement of marine icing phenomena under the presence of a two-phase condition. We have developed a sensor consisting of an electrostatic array and a signal processing based on a decision tree method. A three-element electrostatic array is employed to derive signals having linearly decoupled characteristics from which two key parameters, ice and water accretion layer dimension, can be determined for the purpose of environmental monitoring. The quantified characteristics revealed a correlation with the ice layer thickness in spite of the strong influence from the top water phase layer. The decision tree model established a relationship between the signal characteristics and the two accretion thickness parameters of water and ice layer. Through experimental verification, it has been observed that our sensor array in combination with the decision tree model based signal processing provides a simple practical solution to the challenging field of a two phase composition measurement such as in the marine icing considered in this study. MDPI 2021-01-17 /pmc/articles/PMC7830499/ /pubmed/33477317 http://dx.doi.org/10.3390/s21020612 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Elzaidi, Abdulrazak
Masek, Vlastimil
Bruneau, Stephen
Marine Icing Sensor with Phase Discrimination
title Marine Icing Sensor with Phase Discrimination
title_full Marine Icing Sensor with Phase Discrimination
title_fullStr Marine Icing Sensor with Phase Discrimination
title_full_unstemmed Marine Icing Sensor with Phase Discrimination
title_short Marine Icing Sensor with Phase Discrimination
title_sort marine icing sensor with phase discrimination
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7830499/
https://www.ncbi.nlm.nih.gov/pubmed/33477317
http://dx.doi.org/10.3390/s21020612
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