• DocumentCode
    1934672
  • Title

    Cavitations Monitoring and Diagnosis of Hydropower Turbine on Line Based on Vibration and Ultrasound Acoustic

  • Author

    Liu, Su-yi ; Wang, Shu-qing

  • Author_Institution
    Wuhan Univ. of Sci. & Eng., Wuhan
  • Volume
    5
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    2976
  • Lastpage
    2981
  • Abstract
    The cavitations erosion in hydropower turbines is always a restrict factor of their profitability, which leads to the requirements of periodic inspections and repairs. Detection of cavitations in hydropower turbines with adequate and accurate methods has always been the main goal for hydro-generators researchers in order to diminish or even eliminate its damaging consequences. In the present paper, A multiplex approach was introduced for cavitations detection in which vibratory & ultrasonic sensors are employed and mounted at the lower guide gearing in the direction +X and -Y on the draft tube manhole door and on the head cover etc. A case study of cavitations detection in a large Kaplan turbine is performed in order to detect the cavitations occurrence and to quantify its aggressiveness. Such analysis allows identifying the operating conditions associated with a high erosion risk, which may be taken into account for optimizing turbine operation in order to extend inspections and repairs interval.
  • Keywords
    condition monitoring; hydraulic turbines; maintenance engineering; wear; Kaplan turbine; cavitation diagnosis; cavitation monitoring; cavitations erosion; hydro-generators; hydropower turbine; Acoustical engineering; Blades; Condition monitoring; Frequency; Hydraulic turbines; Hydroelectric power generation; Inspection; Pollution measurement; Ultrasonic imaging; Vibration measurement; Cavitations; Diagnosis; Monitoring; Ultrasound; Vibration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370657
  • Filename
    4370657