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Analysis of the Influencing Factors of the Leak Detection Method Based on the Disturbance-Reflected Signal

Author

Listed:
  • Dongsheng Guo

    (College of Pipeline and Civil Engineering, China University of Petroleum (Huadong), Qingdao 266580, China)

  • Zhaoxue Cui

    (Changqing Engineering Design Co., Ltd., Xi’an 710018, China)

  • Cuiwei Liu

    (College of Pipeline and Civil Engineering, China University of Petroleum (Huadong), Qingdao 266580, China)

  • Yuxing Li

    (College of Pipeline and Civil Engineering, China University of Petroleum (Huadong), Qingdao 266580, China)

Abstract

Leak detection technology, based on the disturbance-reflected signal, can realize pipeline state inspection without relying on the transient characteristics of leakage. However, the lack of research on the factors affecting the detection effect of this method greatly restricts its popularization and application. Therefore, this paper realizes the valve opening and closing through dynamic mesh technology and further establishes a 2D pipeline disturbance and reflection signal detection model. The correctness of the computational fluid dynamics (CFD) model detection mechanism was verified by theoretical analysis and indoor pipe flow experiments. In this process, it was found that reflections from boundaries, such as the pipe end, could also be identified and did not interfere with leak-related signals. In addition, the positioning errors of the leakage hole and the pipe end were 4.447% and 0.121%, respectively, and accurate positioning with zero error was able to be achieved in the calculation results of the CFD model. Finally, the influence factors of the detection effect of this method were analyzed by inputting the determined disturbance signal. Both the disturbance signal characteristics and the leakage hole characteristics affected the reflected signal, and the former played a more prominent role. Surprisingly, the results showed that pipeline flow and pressure had very limited influence on this method.

Suggested Citation

  • Dongsheng Guo & Zhaoxue Cui & Cuiwei Liu & Yuxing Li, 2023. "Analysis of the Influencing Factors of the Leak Detection Method Based on the Disturbance-Reflected Signal," Energies, MDPI, vol. 16(2), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:572-:d:1024343
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    References listed on IDEAS

    as
    1. Silvia Meniconi & Bruno Brunone & Marco Ferrante & Christian Massari, 2011. "Small Amplitude Sharp Pressure Waves to Diagnose Pipe Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 79-96, January.
    2. Liu, Aihua & Chen, Ke & Huang, Xiaofei & Li, Didi & Zhang, Xiaochun, 2021. "Dynamic risk assessment model of buried gas pipelines based on system dynamics," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    3. Xiang, W. & Zhou, W., 2021. "Bayesian network model for predicting probability of third-party damage to underground pipelines and learning model parameters from incomplete datasets," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
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