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Sensor Distribution Design of Travel Time Tomography in Explosion

Optimal sensor distribution in explosion testing is important in saving test costs and improving experiment efficiency. Aiming at travel time tomography in an explosion, an optimizing method in sensor distribution is proposed to improve the inversion stability. The influence factors of inversion sta...

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Detalles Bibliográficos
Autores principales: Guo, Yali, Han, Yan, Wang, Liming, Liu, Linmao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168504/
https://www.ncbi.nlm.nih.gov/pubmed/25029284
http://dx.doi.org/10.3390/s140712687
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author Guo, Yali
Han, Yan
Wang, Liming
Liu, Linmao
author_facet Guo, Yali
Han, Yan
Wang, Liming
Liu, Linmao
author_sort Guo, Yali
collection PubMed
description Optimal sensor distribution in explosion testing is important in saving test costs and improving experiment efficiency. Aiming at travel time tomography in an explosion, an optimizing method in sensor distribution is proposed to improve the inversion stability. The influence factors of inversion stability are analyzed and the evaluating function on optimizing sensor distribution is proposed. This paper presents a sub-region and multi-scale cell partition method, according to the characteristics of a shock wave in an explosion. An adaptive escaping particle swarm optimization algorithm is employed to achieve the optimal sensor distribution. The experimental results demonstrate that optimal sensor distribution has improved both indexes and inversion stability.
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spelling pubmed-41685042014-09-19 Sensor Distribution Design of Travel Time Tomography in Explosion Guo, Yali Han, Yan Wang, Liming Liu, Linmao Sensors (Basel) Article Optimal sensor distribution in explosion testing is important in saving test costs and improving experiment efficiency. Aiming at travel time tomography in an explosion, an optimizing method in sensor distribution is proposed to improve the inversion stability. The influence factors of inversion stability are analyzed and the evaluating function on optimizing sensor distribution is proposed. This paper presents a sub-region and multi-scale cell partition method, according to the characteristics of a shock wave in an explosion. An adaptive escaping particle swarm optimization algorithm is employed to achieve the optimal sensor distribution. The experimental results demonstrate that optimal sensor distribution has improved both indexes and inversion stability. MDPI 2014-07-15 /pmc/articles/PMC4168504/ /pubmed/25029284 http://dx.doi.org/10.3390/s140712687 Text en © 2014 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Guo, Yali
Han, Yan
Wang, Liming
Liu, Linmao
Sensor Distribution Design of Travel Time Tomography in Explosion
title Sensor Distribution Design of Travel Time Tomography in Explosion
title_full Sensor Distribution Design of Travel Time Tomography in Explosion
title_fullStr Sensor Distribution Design of Travel Time Tomography in Explosion
title_full_unstemmed Sensor Distribution Design of Travel Time Tomography in Explosion
title_short Sensor Distribution Design of Travel Time Tomography in Explosion
title_sort sensor distribution design of travel time tomography in explosion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168504/
https://www.ncbi.nlm.nih.gov/pubmed/25029284
http://dx.doi.org/10.3390/s140712687
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AT liulinmao sensordistributiondesignoftraveltimetomographyinexplosion