Pipeline Leak Monitoring System Research Based on Characteristic Curve

Lin Xu; Qin  Zhang; Yi Fan Yu

doi:10.4028/www.scientific.net/AMR.461.407

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 461Pipeline Leak Monitoring System Research Based on...

Pipeline Leak Monitoring System Research Based on Characteristic Curve

Abstract:

To ensure the safe operation of oil and gas pipeline, designed based on the characteristic curve of pipeline leak monitoring system. Detailed real-time data access methods and processes, described RBF neural network algorithms and theory for identifying conditions signal , discussed the pipeline characteristic and device characteristic curve , described the principle to determine the pipeline leak, while the formula for calculating the relevant instructions to do the expansion, through the digital platform interface to obtain a snapshot data improves the reliability and accuracy of the original data. Field tests proved the system's good performance for other crude oil pipeline leak detection to provide guidance.

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Periodical:

Advanced Materials Research (Volume 461)

Pages:

407-410

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.461.407

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Online since:

February 2012

Authors:

Lin Xu, Qin Zhang, Yi Fan Yu

Keywords:

Device Curve, Leak Detection, Location, Pipeline Characteristics, RBF Neural Network

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References

[1] Dingxue Zhang, Xinzhi Liu, Zhihong Guan. RBF neural network algorithm and application [J]. Petrochemical College Journal, 2007, 20 (9): 86 - 88.

Google Scholar

[2] Liang Wei, Laibin Zhang, Caohui Wang. Identify and research of pipeline leak conditions signal under information loss [J]. Journal of university of petroleum: natural science Edition, 2004, 28 (5) : 74-77, 81.

Google Scholar

[3] Xudong Wang, Huihe Shao. RBF neural network theory and its application in control [J]. Information and control, 1997, 26 (4) : 272-284.

Google Scholar

[4] Lining Wang, Li Jian, Shijiu Jin. Heat crude oil pipeline Leakage detection and localization based on transient pressure [J]. Petroleum University, 2000, 21 (4): 93-96.

Google Scholar

[5] Peng Ke, LikunWang, Shijiu Jin. Leakage detection and localization based on the SCADA system [J]. Automation and instrumentation chemical, 2004, 31 (1) : 52-54.

Google Scholar

[6] Haisheng Wang, Buyue Zhang. Design and application of real-time pipeline leak detection system, oil & gas storage and transportation 2001, 20 (12).

Google Scholar