Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics
<p dir="ltr">Monitoring pipeline infrastructure is essential for ensuring safety, efficiency, and environmental sustainability in energy transportation. External disturbances, such as knocking and drilling, are common challenges that can impact pipeline integrity. The proposed approa...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513531946205184 |
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| author | Asan GA Muthalif (22827512) |
| author2 | Bhumiben Ankit Shah (22827515) Kishor Kumar Sadasivuni (8036039) |
| author2_role | author author |
| author_facet | Asan GA Muthalif (22827512) Bhumiben Ankit Shah (22827515) Kishor Kumar Sadasivuni (8036039) |
| author_role | author |
| dc.creator.none.fl_str_mv | Asan GA Muthalif (22827512) Bhumiben Ankit Shah (22827515) Kishor Kumar Sadasivuni (8036039) |
| dc.date.none.fl_str_mv | 2025-07-05T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1177/14613484251348706 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Experimental_data-driven_multimodal_approach_for_detection_and_localization_of_external_disturbances_in_oil_and_gas_pipelines_using_vibration_characteristics/30859865 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Manufacturing engineering Mechanical engineering detection external disturbance localization oil and gas pipeline statistical analysis |
| dc.title.none.fl_str_mv | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Monitoring pipeline infrastructure is essential for ensuring safety, efficiency, and environmental sustainability in energy transportation. External disturbances, such as knocking and drilling, are common challenges that can impact pipeline integrity. The proposed approach develops a multimodal framework for detecting and localizing external disturbances in oil and gas pipelines by integrating statistical methods, signal processing, and advanced diagnostics. The experimental study was conducted on pipelines under three conditions: healthy, knocking, and drilling to assess the capability of the framework to detect and localize external disturbances. The proposed approach effectively classified pipeline conditions. External disturbance localization was precise for knocking disturbances due to their distinct high-frequency characteristics. However, drilling localization was challenging with the current experimental setup. Drilling generated low-frequency vibrations with longer wavelengths, reducing energy loss and broader time responses across closely spaced nodes in the 2-meter pipe setup. This behavior provides insight into the spatial arrangement of the optimal node spacing for effective localization of low-frequency disturbances in long-range pipeline systems.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Low Frequency Noise, Vibration and Active Control<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1177/14613484251348706" target="_blank">https://dx.doi.org/10.1177/14613484251348706</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_7ac27b4a50f91a704a5a1d116546291c |
| identifier_str_mv | 10.1177/14613484251348706 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30859865 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristicsAsan GA Muthalif (22827512)Bhumiben Ankit Shah (22827515)Kishor Kumar Sadasivuni (8036039)EngineeringManufacturing engineeringMechanical engineeringdetectionexternal disturbancelocalizationoil and gas pipelinestatistical analysis<p dir="ltr">Monitoring pipeline infrastructure is essential for ensuring safety, efficiency, and environmental sustainability in energy transportation. External disturbances, such as knocking and drilling, are common challenges that can impact pipeline integrity. The proposed approach develops a multimodal framework for detecting and localizing external disturbances in oil and gas pipelines by integrating statistical methods, signal processing, and advanced diagnostics. The experimental study was conducted on pipelines under three conditions: healthy, knocking, and drilling to assess the capability of the framework to detect and localize external disturbances. The proposed approach effectively classified pipeline conditions. External disturbance localization was precise for knocking disturbances due to their distinct high-frequency characteristics. However, drilling localization was challenging with the current experimental setup. Drilling generated low-frequency vibrations with longer wavelengths, reducing energy loss and broader time responses across closely spaced nodes in the 2-meter pipe setup. This behavior provides insight into the spatial arrangement of the optimal node spacing for effective localization of low-frequency disturbances in long-range pipeline systems.</p><h2>Other Information</h2><p dir="ltr">Published in: Journal of Low Frequency Noise, Vibration and Active Control<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1177/14613484251348706" target="_blank">https://dx.doi.org/10.1177/14613484251348706</a></p>2025-07-05T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1177/14613484251348706https://figshare.com/articles/journal_contribution/Experimental_data-driven_multimodal_approach_for_detection_and_localization_of_external_disturbances_in_oil_and_gas_pipelines_using_vibration_characteristics/30859865CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/308598652025-07-05T03:00:00Z |
| spellingShingle | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics Asan GA Muthalif (22827512) Engineering Manufacturing engineering Mechanical engineering detection external disturbance localization oil and gas pipeline statistical analysis |
| status_str | publishedVersion |
| title | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| title_full | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| title_fullStr | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| title_full_unstemmed | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| title_short | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| title_sort | Experimental data-driven multimodal approach for detection and localization of external disturbances in oil and gas pipelines using vibration characteristics |
| topic | Engineering Manufacturing engineering Mechanical engineering detection external disturbance localization oil and gas pipeline statistical analysis |