• DocumentCode
    3218769
  • Title

    Countermeasures of fast location of pipe bursts in Guangzhou based on neural network technology

  • Author

    Shen, Wang ; Yu, Tu ; Zhihong, Wang ; Yuli, Chen ; Wen, Sun

  • Author_Institution
    Sch. of Civil & Transp. Eng., Guangdong Univ. of Technol., Guangzhou, China
  • fYear
    2011
  • fDate
    22-24 April 2011
  • Firstpage
    5824
  • Lastpage
    5828
  • Abstract
    Recently, with the wide use of on-line monitoring technique in urban water supply networks, pipe network crack diagnosis based on pressure and (or) flow analysis has become a major development direction home and abroad. Meanwhile, in order to solve complex pipe network problems, neural network technology has gained more and more public attention. This paper, in accordance with the actual situations in Guangzhou, through the analysis of the, function, advantages and the results of relevant research of the neural network structure, elaborates the feasibility of its application in the development of the fast locating technology of burst pipes, providing the technical implementation measures for demonstration project.
  • Keywords
    cracks; monitoring; neural nets; pipes; water supply; Guangzhou; flow analysis; neural network technology; online monitoring; pipe bursts; pipe network crack diagnosis; urban water supply networks; Accidents; Analytical models; Artificial neural networks; Biological neural networks; Monitoring; Pipelines; Water pollution; fast location of pipe bursts; neural network technology; water supply network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Technology and Civil Engineering (ICETCE), 2011 International Conference on
  • Conference_Location
    Lushan
  • Print_ISBN
    978-1-4577-0289-1
  • Type

    conf

  • DOI
    10.1109/ICETCE.2011.5774400
  • Filename
    5774400