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Fuzzy Clustering of Vertical Two Phase Flow Regimes Based on Image Processing Technique

[+] Author Affiliations
Soheil Ghanbarzadeh, Pedram Hanafizadeh, Mohammad Hassan Saidi, Ramin Bozorgmehry B.

Sharif University of Technology, Tehran, Iran

Paper No. FEDSM-ICNMM2010-31127, pp. 303-313; 11 pages
doi:10.1115/FEDSM-ICNMM2010-31127
From:
  • ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels
  • ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting: Volume 2, Fora
  • Montreal, Quebec, Canada, August 1–5, 2010
  • Conference Sponsors: Fluids Engineering Division
  • ISBN: 978-0-7918-4949-1 | eISBN: 978-0-7918-3880-8
  • Copyright © 2010 by ASME

abstract

In order to safe design and optimize performance of industrial systems which work under two phase flow conditions, it’s often needed to categorize flow into different regimes. In present work the experiments of two phase flow were done in a large scale test facility with length of 6m and 5cm diameter. Four main flow regimes were observed in vertical air-water two phase flows at moderate superficial velocities of gas and water: Bubbly, Slug, Churn and Annular. Some image processing techniques were used to extract information from each picture. This information include number of bubbles or objects, area, perimeter, height and width of objects (second phase). Also a texture feature extraction procedure was applied to images of different regimes. Some features which were adequate for regime identification were extracted such as Contrast, Energy, Entropy and etc. To identify flow regimes a fuzzy interface was introduced using characteristic of second phase in picture. Also an Adaptive Neuro Fuzzy (ANFIS) was used to identify flow patterns using textural features of images. The experimental results show that these methods can accurately identify the flow patterns in a vertical pipe.

Copyright © 2010 by ASME

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