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Study of Cavitation and Cavitation Erosion Quantitative Method Based on Image Processing Technique

Author(s):


Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2018
Page(s): 1-10
DOI: 10.1155/2018/5317578
Abstract:

Cavitation erosion on the wetted surface of hydraulic machinery is directly related to the cavitation behavior. In this paper, the cavitation behavior and cavitation erosion characteristics on the airfoil surface were observed experimentally, and then, image processing methods for quantifying cavitation structure and cavitation erosion were established. Laser-CCD system was used to obtain the cavitation structure on the airfoil surface and the microtopographies of the cavitation erosion at different magnifications were obtained by SEM. The distribution and shape of cavitation pits were analyzed. An image processing method based on statistical principle was used to analyze the distribution characteristics of the cavitation structure. The mean and mean square value of the cavitation structure were obtained. The average volume and the volume change rate of cavitation cloud in each position of the flow field during a cavitation period were described. According to the characteristics of cavitation pits, an image processing method based on background correction, edge detection, and binary morphology processing was established, and then, the distribution characteristics and the area of the cavitation pits were obtained. Finally, the effectiveness of the methods is verified by the image processing of cavitation pit in different locations on the hydrofoil.

Copyright: © 2018 Dongli Lv et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10176535
  • Published on:
    30/11/2018
  • Last updated on:
    02/06/2021
 
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