• DocumentCode
    3351321
  • Title

    Classification of Database for Dam Safety Monitoring System

  • Author

    Yachao Wang ; Yan Peng ; Fei Zhang ; Hong Yu

  • Author_Institution
    Coll. of Water Conservancy & Hydropower Eng., Hohai Univ., Nanjing
  • fYear
    2009
  • fDate
    27-31 March 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Aiming at the defects & deficiencies existed commonly in the database of dam safety monitoring system used currently such as large data redundancy, bad data consistent, having many difficulties in managing various monitoring data & supporting effectively dam safety monitoring system´s successfully running and unsuitable for update & transform, various information, included in the database of dam safety monitoring system, are discussed further and classified in detail in this paper from the view of hydraulic structure knowledge. The structure of database designed using the method of information classification can improve the defects & deficiencies mentioned above effectively. Compared with the general design method of database, the design method of database classification is much more suitable for designing the database related with hydraulic structure engineering.
  • Keywords
    condition monitoring; dams; data handling; database management systems; safety; structural engineering computing; bad data consistent; dam safety monitoring system; database classification; hydraulic structure knowledge; information classification; large data redundancy; Data engineering; Design engineering; Design methodology; Educational institutions; Image databases; Information analysis; Knowledge management; Monitoring; Safety; Water conservation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-2486-3
  • Electronic_ISBN
    978-1-4244-2487-0
  • Type

    conf

  • DOI
    10.1109/APPEEC.2009.4918218
  • Filename
    4918218