IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v36y2022i7d10.1007_s11269-022-03144-x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03144-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-022-03144-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan Li & Ying Wu & Wenjun Zheng & Changgang Lu, 2021. "A Model-Based Bayesian Framework for Pipeline Leakage Enumeration and Location Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4381-4397, October.
    2. Sang Hyun Kim, 2023. "Generalized Impedance-based Transient Analysis for Multi-branched Pipeline Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1581-1597, March.
    3. Chi Zhang & Martin F. Lambert & Jinzhe Gong & Aaron C. Zecchin & Angus R. Simpson & Mark L. Stephens, 2020. "Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2807-2820, July.
    4. Qianping Zhang & Zhaofei Tian & Shuaijie Lu & Huilun Kang, 2023. "Numerical Simulation of Water Hammer in Pipeline System Using Efficient Wave Tracking Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3053-3068, June.
    5. Mohammad Bostan & Amir Hossein Azimi & Ali Akbar Akhtari & Hossein Bonakdari, 2021. "An Implicit Approach for Numerical Simulation of Water Hammer Induced Pressure in a Straight Pipe," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5155-5167, December.
    6. Caterina Capponi & Silvia Meniconi & Pedro J. Lee & Bruno Brunone & Marco Cifrodelli, 2020. "Time-domain Analysis of Laboratory Experiments on the Transient Pressure Damping in a Leaky Polymeric Pipe," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 501-514, January.
    7. Sanghyun Kim, 2019. "Valve Maneuver Prediction in Simple and Complicated Pipeline Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4671-4685, November.
    8. Molinos-Senante, María & Villegas, Andres & Maziotis, Alexandros, 2019. "Are water tariffs sufficient incentives to reduce water leakages? An empirical approach for Chile," Utilities Policy, Elsevier, vol. 61(C).
    9. M. Fayzul K. Pasha & Matthew Weathers & Brennan Smith, 2020. "Investigating Energy Flow in Water-Energy Storage for Hydropower Generation 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. 34(5), pages 1609-1622, March.
    10. Rejeesh Rayaroth & Sivaradje G, 2019. "Random Bagging Classifier and Shuffled Frog Leaping Based Optimal Sensor Placement for Leakage Detection in WDS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3111-3125, July.
    11. Caroline Blocher & Filippo Pecci & Ivan Stoianov, 2021. "Prior Assumptions for Leak Localisation in Water Distribution Networks with Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(15), pages 5105-5118, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:36:y:2022:i:7:d:10.1007_s11269-022-03144-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.