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Pipeline In-Line Inspection Method, Instrumentation and Data Management
Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defe...
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/PMC8199892/ https://www.ncbi.nlm.nih.gov/pubmed/34205033 http://dx.doi.org/10.3390/s21113862 |
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author | Ma, Qiuping Tian, Guiyun Zeng, Yanli Li, Rui Song, Huadong Wang, Zhen Gao, Bin Zeng, Kun |
author_facet | Ma, Qiuping Tian, Guiyun Zeng, Yanli Li, Rui Song, Huadong Wang, Zhen Gao, Bin Zeng, Kun |
author_sort | Ma, Qiuping |
collection | PubMed |
description | Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline’s integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed. |
format | Online Article Text |
id | pubmed-8199892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81998922021-06-14 Pipeline In-Line Inspection Method, Instrumentation and Data Management Ma, Qiuping Tian, Guiyun Zeng, Yanli Li, Rui Song, Huadong Wang, Zhen Gao, Bin Zeng, Kun Sensors (Basel) Review Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline’s integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed. MDPI 2021-06-03 /pmc/articles/PMC8199892/ /pubmed/34205033 http://dx.doi.org/10.3390/s21113862 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 | Review Ma, Qiuping Tian, Guiyun Zeng, Yanli Li, Rui Song, Huadong Wang, Zhen Gao, Bin Zeng, Kun Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title | Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title_full | Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title_fullStr | Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title_full_unstemmed | Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title_short | Pipeline In-Line Inspection Method, Instrumentation and Data Management |
title_sort | pipeline in-line inspection method, instrumentation and data management |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199892/ https://www.ncbi.nlm.nih.gov/pubmed/34205033 http://dx.doi.org/10.3390/s21113862 |
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