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Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying
In thermal spray process, the characteristics of in-flight particles (velocity and temperature) play an important role regarding the microstructure of the deposit and thus the coating performances. The implementation of diagnostic devices is necessary to measure such characteristics. Many imaging sy...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806362/ https://www.ncbi.nlm.nih.gov/pubmed/37520911 http://dx.doi.org/10.1007/s11666-021-01285-w |
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author | Yao, Yijun Liu, Shaowu Planche, Marie Pierre Deng, Sihao Liao, Hanlin |
author_facet | Yao, Yijun Liu, Shaowu Planche, Marie Pierre Deng, Sihao Liao, Hanlin |
author_sort | Yao, Yijun |
collection | PubMed |
description | In thermal spray process, the characteristics of in-flight particles (velocity and temperature) play an important role regarding the microstructure of the deposit and thus the coating performances. The implementation of diagnostic devices is necessary to measure such characteristics. Many imaging systems and algorithms have been developed for identifying and tracking in-flight particles. However, these current image systems have significant limitations in terms of accuracy for example. One key to solving the tracking problem is to get an algorithm that can effectively distinguish different particles in the same image frame at the same time. This study aims to develop an algorithm capable of identifying a large number of in-flight particles sprayed by thermal process. The results show that the noise and vignettes could be successfully treated, particles are clearly recognized in the background, leading to properly measuring the sizes and positions of the particle versus time. The proposed algorithm has a higher recognition rate and recognition range than other algorithms, which will provide a reasonable basis for subsequent calculation and processing. |
format | Online Article Text |
id | pubmed-8806362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-88063622022-02-02 Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying Yao, Yijun Liu, Shaowu Planche, Marie Pierre Deng, Sihao Liao, Hanlin J Therm Spray Tech Peer Reviewed In thermal spray process, the characteristics of in-flight particles (velocity and temperature) play an important role regarding the microstructure of the deposit and thus the coating performances. The implementation of diagnostic devices is necessary to measure such characteristics. Many imaging systems and algorithms have been developed for identifying and tracking in-flight particles. However, these current image systems have significant limitations in terms of accuracy for example. One key to solving the tracking problem is to get an algorithm that can effectively distinguish different particles in the same image frame at the same time. This study aims to develop an algorithm capable of identifying a large number of in-flight particles sprayed by thermal process. The results show that the noise and vignettes could be successfully treated, particles are clearly recognized in the background, leading to properly measuring the sizes and positions of the particle versus time. The proposed algorithm has a higher recognition rate and recognition range than other algorithms, which will provide a reasonable basis for subsequent calculation and processing. Springer US 2022-02-01 2022 /pmc/articles/PMC8806362/ /pubmed/37520911 http://dx.doi.org/10.1007/s11666-021-01285-w Text en © ASM International 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Peer Reviewed Yao, Yijun Liu, Shaowu Planche, Marie Pierre Deng, Sihao Liao, Hanlin Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title | Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title_full | Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title_fullStr | Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title_full_unstemmed | Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title_short | Application of Image Segmentation to Identify In-flight Particles in Thermal Spraying |
title_sort | application of image segmentation to identify in-flight particles in thermal spraying |
topic | Peer Reviewed |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806362/ https://www.ncbi.nlm.nih.gov/pubmed/37520911 http://dx.doi.org/10.1007/s11666-021-01285-w |
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