• DocumentCode
    1758306
  • Title

    Computational Intelligence for Urban Infrastructure Condition Assessment: Water Transmission and Distribution Systems

  • Author

    Zheng Liu ; Kleiner, Yehuda

  • Author_Institution
    Toyota Technol. Inst., Nagoya, Japan
  • Volume
    14
  • Issue
    12
  • fYear
    2014
  • fDate
    Dec. 2014
  • Firstpage
    4122
  • Lastpage
    4133
  • Abstract
    Water transmission and distribution systems are critical urban infrastructure. The aging of water mains can lead to increased breakage rate, decreased hydraulic capacity, and deterioration of water quality. Condition assessment of water mains encompasses building computational model of failures, discerning distress indicators from inspection, rating health condition, and forecasting future failures. In this process, computational intelligence helps to achieve high-level awareness of system condition and facilitates the decision making in water main renewal and rehabilitation using the combined information from field knowledge, historical records, inspection results, and sensory data. This paper reviews computational approaches to achieve condition assessment of water mains. Inspection and sensor technologies involved in the assessment process are also briefly discussed.
  • Keywords
    ageing; condition monitoring; decision making; fracture; inspection; water supply; breakage rate; computational intelligence; critical urban infrastructure; decision making; distress indicators; field knowledge; historical records; hydraulic capacity; inspection; sensor technologies; sensory data; urban infrastructure condition assessment; water distribution systems; water main renewal; water mains aging; water quality deterioration; water rehabilitation; water transmission systems; Computational modeling; Inspection; Leak detection; Monitoring; Soil; Transient analysis; Computational intelligence; information fusion; water pipe;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2014.2336240
  • Filename
    6855316