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Fast γ Photon Imaging for Inner Surface Defects Detecting
Only a few effective methods can detect internal defects and monitor the internal state of complex structural parts. On the basis of the principle of PET (positron emission computed tomography), a new measurement method, using γ photon to detect defects of an inner surface, is proposed. This method...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662407/ https://www.ncbi.nlm.nih.gov/pubmed/34884138 http://dx.doi.org/10.3390/s21238134 |
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author | Yao, Min Luo, Guangdong Zhao, Min Guo, Ruipeng Liu, Jian |
author_facet | Yao, Min Luo, Guangdong Zhao, Min Guo, Ruipeng Liu, Jian |
author_sort | Yao, Min |
collection | PubMed |
description | Only a few effective methods can detect internal defects and monitor the internal state of complex structural parts. On the basis of the principle of PET (positron emission computed tomography), a new measurement method, using γ photon to detect defects of an inner surface, is proposed. This method has the characteristics of strong penetration, anti-corrosion and anti-interference. With the aim of improving detection accuracy and imaging speed, this study also proposes image reconstruction algorithms, combining the classic FBP (filtered back projection) with MLEM (maximum likelihood expectation Maximization) algorithm. The proposed scheme can reduce the number of iterations required, when imaging, to achieve the same image quality. According to the operational demands of FPGAs (field-programmable gate array), a BPML (back projection maximum likelihood) algorithm is adapted to the structural characteristics of an FPGA, which makes it feasible to test the proposed algorithms therein. Furthermore, edge detection and defect recognition are conducted after reconstructing the inner image. The effectiveness and superiority of the algorithm are verified, and the performance of the FPGA is evaluated by the experiments. |
format | Online Article Text |
id | pubmed-8662407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-86624072021-12-11 Fast γ Photon Imaging for Inner Surface Defects Detecting Yao, Min Luo, Guangdong Zhao, Min Guo, Ruipeng Liu, Jian Sensors (Basel) Article Only a few effective methods can detect internal defects and monitor the internal state of complex structural parts. On the basis of the principle of PET (positron emission computed tomography), a new measurement method, using γ photon to detect defects of an inner surface, is proposed. This method has the characteristics of strong penetration, anti-corrosion and anti-interference. With the aim of improving detection accuracy and imaging speed, this study also proposes image reconstruction algorithms, combining the classic FBP (filtered back projection) with MLEM (maximum likelihood expectation Maximization) algorithm. The proposed scheme can reduce the number of iterations required, when imaging, to achieve the same image quality. According to the operational demands of FPGAs (field-programmable gate array), a BPML (back projection maximum likelihood) algorithm is adapted to the structural characteristics of an FPGA, which makes it feasible to test the proposed algorithms therein. Furthermore, edge detection and defect recognition are conducted after reconstructing the inner image. The effectiveness and superiority of the algorithm are verified, and the performance of the FPGA is evaluated by the experiments. MDPI 2021-12-05 /pmc/articles/PMC8662407/ /pubmed/34884138 http://dx.doi.org/10.3390/s21238134 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yao, Min Luo, Guangdong Zhao, Min Guo, Ruipeng Liu, Jian Fast γ Photon Imaging for Inner Surface Defects Detecting |
title | Fast γ Photon Imaging for Inner Surface Defects Detecting |
title_full | Fast γ Photon Imaging for Inner Surface Defects Detecting |
title_fullStr | Fast γ Photon Imaging for Inner Surface Defects Detecting |
title_full_unstemmed | Fast γ Photon Imaging for Inner Surface Defects Detecting |
title_short | Fast γ Photon Imaging for Inner Surface Defects Detecting |
title_sort | fast γ photon imaging for inner surface defects detecting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8662407/ https://www.ncbi.nlm.nih.gov/pubmed/34884138 http://dx.doi.org/10.3390/s21238134 |
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