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Petroleum pipeline monitoring using an internet of things (IoT) platform
In this study, we present the use of an internet of things (IoT) analytics platform service to mimic real-time pipeline monitoring and determine the location of damage on a pipeline. Pressure pulses, based on the principle of vibration in pipes are used for pipeline monitoring in this study. The pri...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823190/ https://www.ncbi.nlm.nih.gov/pubmed/33521560 http://dx.doi.org/10.1007/s42452-021-04225-z |
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author | Aba, E. N. Olugboji, O. A. Nasir, A. Olutoye, M. A. Adedipe, O. |
author_facet | Aba, E. N. Olugboji, O. A. Nasir, A. Olutoye, M. A. Adedipe, O. |
author_sort | Aba, E. N. |
collection | PubMed |
description | In this study, we present the use of an internet of things (IoT) analytics platform service to mimic real-time pipeline monitoring and determine the location of damage on a pipeline. Pressure pulses, based on the principle of vibration in pipes are used for pipeline monitoring in this study. The principle of time delay between pulse arrivals at sensor positions is also adopted in this study. An Arduino and a Wi-Fi module were combined, programmed and used to produce a wireless communication device which communicates with the ThingSpeak internet of things (IoT) analytics platform. A total of five channels were created on the platform to collect data from the five sensors that were used in the experimental test rig that made use of wireless communication device. Signal data was collected once every 15 s and all the channels were updated every 2 min. ThingSpeak provided instant visualizations of data posted by the wireless communication device. Online analysis and processing of the data was performed as it came in. A second test rig was built that made use of a data logger for processing of data. The measured velocity of pulse propagation using the data logger and air as transport fluid was 355 m/s. The computed estimates of event location for the 50 measurements taken ranged between 4.243 m and 4.246 m. This had a scatter of just 3 mm against the actual measured event location of 4.23 m. The experimental results obtained showed that the performance of the wireless communication device compared satisfactorily with the data logger and is capable of detecting the location of damage on real pipelines when used for real time monitoring. Using this communication device and an analytics platform, real-time monitoring of pipelines can be carried out from any location in the world on any internet-enabled device. |
format | Online Article Text |
id | pubmed-7823190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-78231902021-01-25 Petroleum pipeline monitoring using an internet of things (IoT) platform Aba, E. N. Olugboji, O. A. Nasir, A. Olutoye, M. A. Adedipe, O. SN Appl Sci Research Article In this study, we present the use of an internet of things (IoT) analytics platform service to mimic real-time pipeline monitoring and determine the location of damage on a pipeline. Pressure pulses, based on the principle of vibration in pipes are used for pipeline monitoring in this study. The principle of time delay between pulse arrivals at sensor positions is also adopted in this study. An Arduino and a Wi-Fi module were combined, programmed and used to produce a wireless communication device which communicates with the ThingSpeak internet of things (IoT) analytics platform. A total of five channels were created on the platform to collect data from the five sensors that were used in the experimental test rig that made use of wireless communication device. Signal data was collected once every 15 s and all the channels were updated every 2 min. ThingSpeak provided instant visualizations of data posted by the wireless communication device. Online analysis and processing of the data was performed as it came in. A second test rig was built that made use of a data logger for processing of data. The measured velocity of pulse propagation using the data logger and air as transport fluid was 355 m/s. The computed estimates of event location for the 50 measurements taken ranged between 4.243 m and 4.246 m. This had a scatter of just 3 mm against the actual measured event location of 4.23 m. The experimental results obtained showed that the performance of the wireless communication device compared satisfactorily with the data logger and is capable of detecting the location of damage on real pipelines when used for real time monitoring. Using this communication device and an analytics platform, real-time monitoring of pipelines can be carried out from any location in the world on any internet-enabled device. Springer International Publishing 2021-01-23 2021 /pmc/articles/PMC7823190/ /pubmed/33521560 http://dx.doi.org/10.1007/s42452-021-04225-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Aba, E. N. Olugboji, O. A. Nasir, A. Olutoye, M. A. Adedipe, O. Petroleum pipeline monitoring using an internet of things (IoT) platform |
title | Petroleum pipeline monitoring using an internet of things (IoT) platform |
title_full | Petroleum pipeline monitoring using an internet of things (IoT) platform |
title_fullStr | Petroleum pipeline monitoring using an internet of things (IoT) platform |
title_full_unstemmed | Petroleum pipeline monitoring using an internet of things (IoT) platform |
title_short | Petroleum pipeline monitoring using an internet of things (IoT) platform |
title_sort | petroleum pipeline monitoring using an internet of things (iot) platform |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7823190/ https://www.ncbi.nlm.nih.gov/pubmed/33521560 http://dx.doi.org/10.1007/s42452-021-04225-z |
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