• DocumentCode
    3581547
  • Title

    A leakage detection system on the Water Pipe Network through Support Vector Machine method

  • Author

    Salam, A. Ejah Umraeni ; Tola, Muh ; Selintung, Mary ; Maricar, Farouk

  • Author_Institution
    Fak. Tek., Univ. Hasanuddin, Makassar, Indonesia
  • fYear
    2014
  • Firstpage
    161
  • Lastpage
    165
  • Abstract
    Clean Water is the primary and basic need for human. Thus, the provision of it has to be assured by preserving the quality, quantity, and also the pressure. However, in fact, there are many leakage cases in the distribution process which become the world´s problem. One of the causes of the leakage, technically, is the leakage on the pipes. The leaky pipe changed the pressure on each junction / node in water pipe network. The pattern of the pressure changes, then, is able to be analyzed computationally to detect the location and the size of the leakage. In this research, there is a detector of the leakage that will be used computerized through Support Vector Machine (SVM) method. As the research material, there is Water Pipe Network System in Taman Khayangan Resident Makassar which was made by using EPANET 2.0 software. The data of the Pipe Network System is obtained from the Data of Drinking Water Local Company (PDAM) of Makassar. The output of this Leakage Detection System is in the form of model which detects the size and the location of the leakage on the pipe. The results of the simulation showed that the SVM method is relatively accurate in predicting by resulting the RMSE average of 0.06785 for the leakage size and RMSE = 0.1382 for the leakage location.
  • Keywords
    mean square error methods; pipes; production engineering computing; support vector machines; water quality; EPANET 2.0 software; RMSE; SVM method; Taman Khayangan Resident Makassar; leakage detection system; support vector machine; water pipe network; Detectors; Monitoring; Reliability; Support vector machines; EPANET 2.0; Leakage of pipelines; Root Mean Square Error (RMSE); Support Vector machine (SVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Informatics (MICEEI), 2014 Makassar International Conference on
  • Print_ISBN
    978-1-4799-6725-4
  • Type

    conf

  • DOI
    10.1109/MICEEI.2014.7067331
  • Filename
    7067331