• DocumentCode
    596538
  • Title

    Visibility graph analysis of fluid flow signals

  • Author

    Zhongke Gao ; Lingchao Ji

  • Author_Institution
    Sch. of Electr. Eng. & Autom., Tianjin Univ., Tianjin, China
  • fYear
    2012
  • fDate
    18-20 Oct. 2012
  • Firstpage
    44
  • Lastpage
    47
  • Abstract
    Visibility graphs have established themselves in recent years as being particularly suitable and flexible for analyzing signals measured from complex natural and artificial systems. Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visibility graph to analyze the signals measured from experiment two-phase flow. We first introduce the inclined oil-water two-phase flow experiment and data acquisition. Then we present the algorithm for constructing visibility graphs from signals. Finally, we infer and analyze visibility graphs from signals measured under different fluid flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish and characterize different oil-water two-phase flow patterns. In this regard, visibility graph could be a useful tool for processing experimental signals.
  • Keywords
    complex networks; flow measurement; graph theory; oils; stratified flow; water; complex artificial systems; complex natural systems; complicated fluid flow; data acquisition; fluid flow conditions; fluid flow signals; inclined oil-water two phase flow experiment; visibility graph analysis; Complex networks; Data acquisition; Dispersion; Educational institutions; Fluid flow measurement; Time series analysis; Voltage measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-1743-6
  • Type

    conf

  • DOI
    10.1109/ICACI.2012.6463119
  • Filename
    6463119