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An Accurate Leakage Localization Method for Water Supply Network Based on Deep Learning Network

Author

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  • Juan Li

    (Jilin University)

  • Wenjun Zheng

    (Jilin University)

  • Changgang Lu

    (Jilin University)

Abstract

In the water supply network, leakage of pipes will cause water loss and increase the risk of environmental pollution. For water supply systems, identifying the leak point can improve the efficiency of pipeline leak repair. Most existing leak location methods can only locate the leak point approximately at the node or pipe section of the pipe network but cannot locate the specific location of the pipe section. This paper presents a framework for accurate water supply network leakage location based on Residual Network (ResNet). This study proposes a leak localization idea with a parallel classification and regression process that enables the framework to pinpoint the exact position of leak points in the pipeline. Furthermore, a multi-supervision mechanism is designed in the regression process to speed up the model’s convergence. For a pipe network containing 40 pipes, the positioning accuracy of the pipe section is 0.94, and the MSE of the specific location of the leakage point is 0.000435. For the pipe network containing 117 pipes, the positioning accuracy of the pipe section is 0.91. The MSE of the specific location of the leakage point is 0.0009177. Experiments confirm the robustness and applicability of the framework.

Suggested Citation

  • Juan Li & Wenjun Zheng & Changgang Lu, 2022. "An Accurate Leakage Localization Method for Water Supply Network Based on Deep Learning Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2309-2325, May.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:7:d:10.1007_s11269-022-03144-x
    DOI: 10.1007/s11269-022-03144-x
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    References listed on IDEAS

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    1. Huan-Feng Duan, 2018. "Accuracy and Sensitivity Evaluation of TFR Method for Leak Detection in Multiple-Pipeline Water Supply Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(6), pages 2147-2164, April.
    2. Xiang Xie & Dibo Hou & Xiaoyu Tang & Hongjian Zhang, 2019. "Leakage Identification in Water Distribution Networks with Error Tolerance Capability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1233-1247, February.
    3. Roberto del Teso & Elena Gómez & Elvira Estruch-Juan & Enrique Cabrera, 2019. "Topographic Energy Management in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4385-4400, September.
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    Cited by:

    1. Sehyeong Kim & Sanghoon Jun & Donghwi Jung, 2022. "Ensemble CNN Model for Effective Pipe Burst Detection in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(13), pages 5049-5061, October.
    2. Li, Pengyu & Wang, Xiufang & Jiang, Chunlei & Bi, Hongbo & Liu, Yongzhi & Yan, Wendi & Zhang, Cong & Dong, Taiji & Sun, Yu, 2024. "Advanced transformer model for simultaneous leakage aperture recognition and localization in gas pipelines," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Wang Pengfei & Jiang Zhiqiang & Duan Jiefeng, 2023. "Burst Analysis of Water Supply Pipe Based on Hydrodynamic Simulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(5), pages 2161-2179, March.
    4. Irene Marzola & Stefano Alvisi & Marco Franchini, 2022. "A Comparison of Model-Based Methods for Leakage Localization in Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5711-5727, November.

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