Analysis of Methods for Leak Detection and Monitoring the Main Gas Pipeline Sections

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dc.citation.epage80
dc.citation.issue2
dc.citation.journalTitleЕнергетика та системи керування
dc.citation.spage73
dc.citation.volume10
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorДанильців, Богдан
dc.contributor.authorХимко, Ольга
dc.contributor.authorDanyltsiv, Bohdan
dc.contributor.authorKhymko, Olga
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-10-20T09:16:11Z
dc.date.created2024-02-27
dc.date.issued2024-02-27
dc.description.abstractУ статті проаналізовано методи виявлення витоків та моніторингу стану ділянок магістральних газопроводів. Подано розширену класифікацію методів за додатковими параметрами: режимом роботи (стаціонарний, нестаціонарний) та типом виявлення витоку (виявлення наявності, локалізація місця, визначення об’єму). На основі порівняльного аналізу методів за критеріями чутливості, надійності, точності локалізації, часу реакції та вартості впровадження встановлено, що для нестаціонарного режиму роботи та довгих трубопроводів найефективнішою є комбінація методу негативної хвилі тиску із розширеною системою моделювання у реальному часі. Визначено перспективні напрями подальшого розвитку систем виявлення витоків, що передбачають удосконалення математичних моделей, інтеграцію методів штучного інтелекту, покращення технічних засобів та програмного забезпечення.
dc.description.abstractThe paper analyzes the existing methods for leak detection and monitoring the main gas pipeline sections. An extended classification of methods is presented based on the additional parameters: operating mode (steady-state, non-steady-state) and type of leak detection (presence detection, location identification, volume determination). Based on the comparative analysis of methods according to criteria of sensitivity, reliability, localization accuracy, response time, and implementation cost, the negative pressure wave method with an extended real-time modeling system was established to be the most effective combination for non-steady-state operation mode and long pipelines. Promising areas for further development of leak detection systems have been identified, including improvement of mathematical models, integration of artificial intelligence methods, enhancement of technical equipment and software.
dc.format.extent73-80
dc.format.pages8
dc.identifier.citationDanyltsiv B. Analysis of Methods for Leak Detection and Monitoring the Main Gas Pipeline Sections / Bohdan Danyltsiv, Olga Khymko // Energy Engineering and Control Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 10. — No 2. — P. 73–80.
dc.identifier.citationenDanyltsiv B. Analysis of Methods for Leak Detection and Monitoring the Main Gas Pipeline Sections / Bohdan Danyltsiv, Olga Khymko // Energy Engineering and Control Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 10. — No 2. — P. 73–80.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/113844
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofЕнергетика та системи керування, 2 (10), 2024
dc.relation.ispartofEnergy Engineering and Control Systems, 2 (10), 2024
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dc.relation.references[4] Bezgachnyuk Yurii, Shtaier Lidiia. Overview of the Current State of Pipeline Leak Control Methods. International Science Journal of Engineering & Agriculture. Vol. 3, No. 3, 2024, pp. 43-50. https://doi.org/10.46299/j.isjea.20240303.04
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dc.relation.references[6] Chen, P.; Li, R.; Jia, G.; Lan, H.; Fu, K.; Liu, X. A Decade Review of the Art of Inspection and Monitoring Technologies for Long-Distance Oil and Gas Pipelines in Permafrost Areas. Energies 2023, 16, 1751. https://doi.org/10.3390/en16041751
dc.relation.references[7] Fu, H., Ling, K., & Pu, H. (2022). Identifying two-point leakages in parallel pipelines based on flow parameter analysis. Journal of Pipeline Science and Engineering, 2(1), 100052. https://doi.org/10.1016/j.jpse.2022.02.001
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dc.relation.references[9] Boxiang Liu, Zhu Jiang, Wei Nie (2021). Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave. Hindawi Journal of Sensors Volume 2021, Article ID 8699362, 19 pages. https://doi.org/10.1155/2021/8699362
dc.relation.references[10] Chang Chang, Xiangli Li , Lin Duanmu, Hongwei Li, Wenbin Zhou. Locating leakage in pipelines based on the adjoint equation of inversion modeling. Heliyon 9 (2023) e17270. https://doi.org/10.1016/j.heliyon.2023.e17270
dc.relation.references[11] Raheleh Jafari, Sina Razvarz, Cristóbal Vargas-Jarillo, Alexander Gegov, and Farzad Arabikhan. Pipeline Leak Detection and Estimation Using Fuzzy PID Observer. Electronics 2022, 11, 152. https://doi.org/10.3390/electronics11010152
dc.relation.references[12] Dr Alex Souza de Joode, Andrew Hoffman. Pipeline Leak Detection and Theft Detection Using Rarefaction Waves. 6th Pipeline Technology Conference 2011.
dc.relation.references[13] Dandi Yang. Establishment of leakage detection model for oil and gas pipeline based on VMD-MD-1DCNN. 2022 Eng. Res. Express 4 025051. https://doi.org/10.1088/2631-8695/ac769e
dc.relation.references[14] Lijuan Zhu, Dongmei Wang1, Jikang Yue, Jingyi Lu and Gongfa Li. Leakage detection method of natural gas pipeline combining improved variational mode decomposition and Lempel–Ziv complexity analysis. Transactions of the Institute of Measurement and Control 2022, Vol. 44(15) 2865–2876 The Author(s) 2022 Article reuse guidelines: sagepub.com/journals-permissions https://doi.org/10.1177/01423312221088080
dc.relation.references[15] V. Muralidharan, S. Prabhavathy, L. Pavithra, V. Nithya. IoT Based Smart Monitoring and Controlling System for Gas Leakage in Industries. Volume 9 Issue 9, 38-46, September 2022. https://doi.org/10.14445/23488379/IJEEE-V9I9P105
dc.relation.references[16] Te-Kwei Wang, Yu-Hsun Lin, Jian-Yuan Shen. Developing and Implementing an AI-Based Leak Detection System in a Long-Distance Gas Pipeline. Advances in Technology Innovation, vol. 7, no. 3, 2022, pp. 169-180. https://doi.org/10.46604/aiti.2022.8904
dc.relation.references[17] Yao-bin Li , Qing-Yun Fu , and Xin Guo. Research on the Propagation of Acoustic Signal and Attenuation Change Law of Gas Pipeline Double-Point Leakage. Hindawi Shock and Vibration Volume 2023, Article ID 7725366, 9 pages. https://doi.org/10.1155/2023/7725366
dc.relation.references[18] Feng Wang, Zhen Liu, Xiao Zhou, Shiyi Li, Xinyu Yuan, Yixin Zhang, Liyang Shao c, Xuping Zhang. Oil and Gas Pipeline Leakage Recognition Based on Distributed Vibration and Temperature Information Fusion. Results in Optics Volume 5 , December 2021, 100131. https://doi.org/10.1016/j.rio.2021.100131
dc.relation.references[19] Kegang Ling, Guoqing Han and Xiao Ni, Chunming Xu, Jun He, Peng Pei, and Jun Ge. A New Method for Leak Detection in Gas Pipelines. April 2015, Oil and Gas Facilities.
dc.relation.references[20] Danial Waleed, Syed Hamdan Mustafa, Shayok Mukhopadhyay, Mamoun Abdel-Hafez, Mohammad A. Jaradat, Kevin Rose Dias, Fahad Arif, Jawwad Imtiaz Ahmed. An in-pipe leak detection robot with a neural-network based leak verification system.
dc.relation.referencesen[1] The World Factbook - Central Intelligence Agency. www.cia.gov. Original archive for August 21, 2016.
dc.relation.referencesen[2] K. Sachedina and A. Mohany. A review of pipeline monitoring and periodic inspection methods. Pipeline Science and Technology. 2018; 2(3): 187-203. https://doi.org/10.28999/2514-541X-2018-2-3-187-201
dc.relation.referencesen[3] Jun Zhang, Peter Han, Michael Twomey. Overview of pipeline leak detection technologies. Atmos International 14607 San Pedro Avenue Suite 290 San Antonio, TX 78232 USA
dc.relation.referencesen[4] Bezgachnyuk Yurii, Shtaier Lidiia. Overview of the Current State of Pipeline Leak Control Methods. International Science Journal of Engineering & Agriculture. Vol. 3, No. 3, 2024, pp. 43-50. https://doi.org/10.46299/j.isjea.20240303.04
dc.relation.referencesen[5] Naga Venkata Saidileep Korlapati, Faisal Khan, Quddus Noor, Saadat Mirza, Sreeram Vaddiraju. Review and analysis of pipeline leak detection methods. Journal of Pipeline Science and Engineering Volume 2, Issue 4, December 2022, 100074. https://doi.org/10.1016/j.jpse.2022.100074
dc.relation.referencesen[6] Chen, P.; Li, R.; Jia, G.; Lan, H.; Fu, K.; Liu, X. A Decade Review of the Art of Inspection and Monitoring Technologies for Long-Distance Oil and Gas Pipelines in Permafrost Areas. Energies 2023, 16, 1751. https://doi.org/10.3390/en16041751
dc.relation.referencesen[7] Fu, H., Ling, K., & Pu, H. (2022). Identifying two-point leakages in parallel pipelines based on flow parameter analysis. Journal of Pipeline Science and Engineering, 2(1), 100052. https://doi.org/10.1016/j.jpse.2022.02.001
dc.relation.referencesen[8] Riaz, M., Ahmad, I., Khan, M.N., Mond, M.A. and Mir, A. (2020) ‘Volumetric flow and pressure gradient-based leak detection system for oil and gas pipelines’, Int. J. Oil, Gas and Coal Technology, Vol. 25, No. 3, pp. 340–356. https://doi.org/10.1504/IJOGCT.2020.110386
dc.relation.referencesen[9] Boxiang Liu, Zhu Jiang, Wei Nie (2021). Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave. Hindawi Journal of Sensors Volume 2021, Article ID 8699362, 19 pages. https://doi.org/10.1155/2021/8699362
dc.relation.referencesen[10] Chang Chang, Xiangli Li , Lin Duanmu, Hongwei Li, Wenbin Zhou. Locating leakage in pipelines based on the adjoint equation of inversion modeling. Heliyon 9 (2023) e17270. https://doi.org/10.1016/j.heliyon.2023.e17270
dc.relation.referencesen[11] Raheleh Jafari, Sina Razvarz, Cristóbal Vargas-Jarillo, Alexander Gegov, and Farzad Arabikhan. Pipeline Leak Detection and Estimation Using Fuzzy PID Observer. Electronics 2022, 11, 152. https://doi.org/10.3390/electronics11010152
dc.relation.referencesen[12] Dr Alex Souza de Joode, Andrew Hoffman. Pipeline Leak Detection and Theft Detection Using Rarefaction Waves. 6th Pipeline Technology Conference 2011.
dc.relation.referencesen[13] Dandi Yang. Establishment of leakage detection model for oil and gas pipeline based on VMD-MD-1DCNN. 2022 Eng. Res. Express 4 025051. https://doi.org/10.1088/2631-8695/ac769e
dc.relation.referencesen[14] Lijuan Zhu, Dongmei Wang1, Jikang Yue, Jingyi Lu and Gongfa Li. Leakage detection method of natural gas pipeline combining improved variational mode decomposition and Lempel–Ziv complexity analysis. Transactions of the Institute of Measurement and Control 2022, Vol. 44(15) 2865–2876 The Author(s) 2022 Article reuse guidelines: sagepub.com/journals-permissions https://doi.org/10.1177/01423312221088080
dc.relation.referencesen[15] V. Muralidharan, S. Prabhavathy, L. Pavithra, V. Nithya. IoT Based Smart Monitoring and Controlling System for Gas Leakage in Industries. Volume 9 Issue 9, 38-46, September 2022. https://doi.org/10.14445/23488379/IJEEE-V9I9P105
dc.relation.referencesen[16] Te-Kwei Wang, Yu-Hsun Lin, Jian-Yuan Shen. Developing and Implementing an AI-Based Leak Detection System in a Long-Distance Gas Pipeline. Advances in Technology Innovation, vol. 7, no. 3, 2022, pp. 169-180. https://doi.org/10.46604/aiti.2022.8904
dc.relation.referencesen[17] Yao-bin Li , Qing-Yun Fu , and Xin Guo. Research on the Propagation of Acoustic Signal and Attenuation Change Law of Gas Pipeline Double-Point Leakage. Hindawi Shock and Vibration Volume 2023, Article ID 7725366, 9 pages. https://doi.org/10.1155/2023/7725366
dc.relation.referencesen[18] Feng Wang, Zhen Liu, Xiao Zhou, Shiyi Li, Xinyu Yuan, Yixin Zhang, Liyang Shao c, Xuping Zhang. Oil and Gas Pipeline Leakage Recognition Based on Distributed Vibration and Temperature Information Fusion. Results in Optics Volume 5 , December 2021, 100131. https://doi.org/10.1016/j.rio.2021.100131
dc.relation.referencesen[19] Kegang Ling, Guoqing Han and Xiao Ni, Chunming Xu, Jun He, Peng Pei, and Jun Ge. A New Method for Leak Detection in Gas Pipelines. April 2015, Oil and Gas Facilities.
dc.relation.referencesen[20] Danial Waleed, Syed Hamdan Mustafa, Shayok Mukhopadhyay, Mamoun Abdel-Hafez, Mohammad A. Jaradat, Kevin Rose Dias, Fahad Arif, Jawwad Imtiaz Ahmed. An in-pipe leak detection robot with a neural-network based leak verification system.
dc.relation.urihttps://doi.org/10.28999/2514-541X-2018-2-3-187-201
dc.relation.urihttps://doi.org/10.46299/j.isjea.20240303.04
dc.relation.urihttps://doi.org/10.1016/j.jpse.2022.100074
dc.relation.urihttps://doi.org/10.3390/en16041751
dc.relation.urihttps://doi.org/10.1016/j.jpse.2022.02.001
dc.relation.urihttps://doi.org/10.1504/IJOGCT.2020.110386
dc.relation.urihttps://doi.org/10.1155/2021/8699362
dc.relation.urihttps://doi.org/10.1016/j.heliyon.2023.e17270
dc.relation.urihttps://doi.org/10.3390/electronics11010152
dc.relation.urihttps://doi.org/10.1088/2631-8695/ac769e
dc.relation.urihttps://doi.org/10.1177/01423312221088080
dc.relation.urihttps://doi.org/10.14445/23488379/IJEEE-V9I9P105
dc.relation.urihttps://doi.org/10.46604/aiti.2022.8904
dc.relation.urihttps://doi.org/10.1155/2023/7725366
dc.relation.urihttps://doi.org/10.1016/j.rio.2021.100131
dc.rights.holder© Національний університет “Львівська політехніка”, 2024
dc.subjectмагістральний газопровід
dc.subjectвиявлення витоків
dc.subjectмоніторинг стану
dc.subjectнегативна хвиля тиску
dc.subjectмоделювання у реальному часі
dc.subjectнестаціонарний режим
dc.subjectmain gas pipeline
dc.subjectleak detection
dc.subjectcondition monitoring
dc.subjectnegative pressure wave
dc.subjectreal-time modeling
dc.subjectnon-steady-state mode
dc.titleAnalysis of Methods for Leak Detection and Monitoring the Main Gas Pipeline Sections
dc.title.alternativeАналіз методів виявлення витоків та моніторингу стану ділянок магістральних газопроводів
dc.typeArticle

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Energy Engineering and Control Systems. – 2024. – Vol. 10, No. 2