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Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array

This paper presents a study of aero-engine exhaust gas electrostatic sensor array to estimate the spatial position, charge amount and velocity of charged particle. Firstly, this study establishes a mathematical model to analyze the inducing characteristics and obtain the spatial sensitivity distribu...

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Detalles Bibliográficos
Autores principales: Guo, Jiachen, Zhong, Zhirong, Jiang, Heng, Zuo, Hongfu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455019/
https://www.ncbi.nlm.nih.gov/pubmed/34100331
http://dx.doi.org/10.1177/00368504211023691
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author Guo, Jiachen
Zhong, Zhirong
Jiang, Heng
Zuo, Hongfu
author_facet Guo, Jiachen
Zhong, Zhirong
Jiang, Heng
Zuo, Hongfu
author_sort Guo, Jiachen
collection PubMed
description This paper presents a study of aero-engine exhaust gas electrostatic sensor array to estimate the spatial position, charge amount and velocity of charged particle. Firstly, this study establishes a mathematical model to analyze the inducing characteristics and obtain the spatial sensitivity distribution of sensor array. Then, Tikhonov regularization and compressed sensing are used to estimate the spatial position and charge amount of particle based on the obtained sensitivity distribution; cross-correlation algorithm is used to determine particle’s velocity. An oil calibration test rig is established to verify the proposed methods. Thirteen spatial positions are selected as the test points. The estimation errors of spatial positions and charge amounts are both within 5% when the particles are locating at central area. The errors are higher when the particles are closer to the wall and may exceed 10%. The estimation errors of velocities by using cross-correlation are all within 2%. An air-gun test rig is further established to simulate the high velocity condition and distinguish different kinds of particles such as metal particles and non-metal particles.
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spelling pubmed-104550192023-08-26 Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array Guo, Jiachen Zhong, Zhirong Jiang, Heng Zuo, Hongfu Sci Prog Article This paper presents a study of aero-engine exhaust gas electrostatic sensor array to estimate the spatial position, charge amount and velocity of charged particle. Firstly, this study establishes a mathematical model to analyze the inducing characteristics and obtain the spatial sensitivity distribution of sensor array. Then, Tikhonov regularization and compressed sensing are used to estimate the spatial position and charge amount of particle based on the obtained sensitivity distribution; cross-correlation algorithm is used to determine particle’s velocity. An oil calibration test rig is established to verify the proposed methods. Thirteen spatial positions are selected as the test points. The estimation errors of spatial positions and charge amounts are both within 5% when the particles are locating at central area. The errors are higher when the particles are closer to the wall and may exceed 10%. The estimation errors of velocities by using cross-correlation are all within 2%. An air-gun test rig is further established to simulate the high velocity condition and distinguish different kinds of particles such as metal particles and non-metal particles. SAGE Publications 2021-06-08 /pmc/articles/PMC10455019/ /pubmed/34100331 http://dx.doi.org/10.1177/00368504211023691 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Article
Guo, Jiachen
Zhong, Zhirong
Jiang, Heng
Zuo, Hongfu
Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title_full Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title_fullStr Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title_full_unstemmed Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title_short Identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
title_sort identification methods of charged particles based on aero-engine exhaust gas electrostatic sensor array
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10455019/
https://www.ncbi.nlm.nih.gov/pubmed/34100331
http://dx.doi.org/10.1177/00368504211023691
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