Identification of different flow regimes in industrial systems operating under two-phase flow conditions is necessary in order to safely design and optimize their performance. In the present work, experiments on two-phase flow have been performed in a large scale test facility with the length of 6 m and diameter of 5 cm. Four main flow regimes have been observed in vertical air-water two-phase flow at moderate superficial velocities of gas and water namely: Bubbly, Slug, Churn, and Annular. An image processing technique was used to extract information from each picture. This information includes the number of bubbles or objects, area, perimeter, as well as the height and width of objects (second phase). In addition, 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, etc. To identify flow regimes, a fuzzy interface was introduced using characteristic of second phase in picture. Furthermore, 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.
Skip Nav Destination
e-mail: saman@sharif.edu
Article navigation
June 2012
Multiphase Flows
Intelligent Image-Based Gas-Liquid Two-Phase Flow Regime Recognition
Soheil Ghanbarzadeh,
Soheil Ghanbarzadeh
PhD Student of Petroleum Engineering
Department of Petroleum and Geosystems Engineering,
University of Texas at Austin
, Austin, TX 78712-1585
Search for other works by this author on:
Pedram Hanafizadeh,
Pedram Hanafizadeh
Postdoctoral Fellow
Search for other works by this author on:
Mohammad Hassan Saidi
Mohammad Hassan Saidi
Multiphase Flow Research Group, Center of Excellence in Energy Conversion,
e-mail: saman@sharif.edu
School of Mechanical Engineering
, Sharif University of Technology
, P. O. Box: 11155-9567, Azadi Street, Tehran, Iran
Search for other works by this author on:
Soheil Ghanbarzadeh
PhD Student of Petroleum Engineering
Department of Petroleum and Geosystems Engineering,
University of Texas at Austin
, Austin, TX 78712-1585
Pedram Hanafizadeh
Postdoctoral Fellow
Mohammad Hassan Saidi
Multiphase Flow Research Group, Center of Excellence in Energy Conversion,
School of Mechanical Engineering
, Sharif University of Technology
, P. O. Box: 11155-9567, Azadi Street, Tehran, Iran
e-mail: saman@sharif.edu
J. Fluids Eng. Jun 2012, 134(6): 061302 (10 pages)
Published Online: May 29, 2012
Article history
Received:
October 19, 2011
Revised:
April 11, 2012
Online:
May 29, 2012
Published:
May 29, 2012
Citation
Ghanbarzadeh, S., Hanafizadeh, P., and Hassan Saidi, M. (May 29, 2012). "Intelligent Image-Based Gas-Liquid Two-Phase Flow Regime Recognition." ASME. J. Fluids Eng. June 2012; 134(6): 061302. https://doi.org/10.1115/1.4006613
Download citation file:
Get Email Alerts
Related Articles
An Approach to Seizure Onset Detection Using Fuzzy Logic Based on Seizure Evolution in Intracranial EEG
J. Med. Devices (June,2011)
Development of a Self-Organized Neuro-Fuzzy Model for System Identification
J. Vib. Acoust (August,2007)
Commutation Sparking Image Monitoring for DC Motor
J. Manuf. Sci. Eng (April,2012)
New Method to Determine the Velocities of Particles on a Solid Propellant Surface in a Solid Rocket Motor
J. Heat Transfer (September,2005)
Related Proceedings Papers
Related Chapters
Interval Type-2 Fuzzy Logic for Improving Feature Extraction and Response Integration in Modular Neural Networks for Image Recognition
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Mouth's Action Units Recognition Base on Non-Frontal View 3D Images
International Conference on Computer Engineering and Technology, 3rd (ICCET 2011)
Fuzzy Logic Voltage Flicker Estimation Using Hilbert Transform
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)