Marine Icing Sensor with Phase Discrimination.

decision tree method electrostatic sensor array marine icing

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
17 Jan 2021
Historique:
received: 20 11 2020
revised: 12 01 2021
accepted: 14 01 2021
entrez: 22 1 2021
pubmed: 23 1 2021
medline: 23 1 2021
Statut: epublish

Résumé

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.

Identifiants

pubmed: 33477317
pii: s21020612
doi: 10.3390/s21020612
pmc: PMC7830499
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Sensors (Basel). 2015 Mar 19;15(3):6688-98
pubmed: 25808770
Shanghai Arch Psychiatry. 2015 Apr 25;27(2):130-5
pubmed: 26120265

Auteurs

Abdulrazak Elzaidi (A)

Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.

Vlastimil Masek (V)

Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.

Stephen Bruneau (S)

Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.

Classifications MeSH