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Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction

Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in the...

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Detalles Bibliográficos
Autores principales: Wang, Yu, Li, Xueyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179036/
https://www.ncbi.nlm.nih.gov/pubmed/32290126
http://dx.doi.org/10.3390/ma13071786
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author Wang, Yu
Li, Xueyi
author_facet Wang, Yu
Li, Xueyi
author_sort Wang, Yu
collection PubMed
description Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in the turn generated ultrasonic guided wave signals in the elbow. Then, the wavefront flight time at each grid node in the known sound field were computed using the fast-marching algorithm. Finally, an elbow wall thickness map reconstruction technique based on the sparse inversion method was proposed to identify elbow defects. Compared with the traditional elbow defect identification technology, this technology can not only detect the existence of the defect but also accurately locate the defect position.
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spelling pubmed-71790362020-04-28 Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction Wang, Yu Li, Xueyi Materials (Basel) Article Continuous monitoring for defects in oil and gas pipelines is important for leakage prevention. This paper proposes a new kind of pipe elbow damage identification technique, which consists of three processes. First, piezoelectric sensors evenly arranged along the circumference of the pipeline in the turn generated ultrasonic guided wave signals in the elbow. Then, the wavefront flight time at each grid node in the known sound field were computed using the fast-marching algorithm. Finally, an elbow wall thickness map reconstruction technique based on the sparse inversion method was proposed to identify elbow defects. Compared with the traditional elbow defect identification technology, this technology can not only detect the existence of the defect but also accurately locate the defect position. MDPI 2020-04-10 /pmc/articles/PMC7179036/ /pubmed/32290126 http://dx.doi.org/10.3390/ma13071786 Text en © 2020 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Yu
Li, Xueyi
Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title_full Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title_fullStr Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title_full_unstemmed Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title_short Elbow Damage Identification Technique Based on Sparse Inversion Image Reconstruction
title_sort elbow damage identification technique based on sparse inversion image reconstruction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7179036/
https://www.ncbi.nlm.nih.gov/pubmed/32290126
http://dx.doi.org/10.3390/ma13071786
work_keys_str_mv AT wangyu elbowdamageidentificationtechniquebasedonsparseinversionimagereconstruction
AT lixueyi elbowdamageidentificationtechniquebasedonsparseinversionimagereconstruction