NDLI: Simple model of equilibrium froth height for foams: an application for CNN image analysis

Content Provider	IEEE Xplore Digital Library
Author	Zimmermann, W.B.J. Jeanmeure, L.F.C.
Copyright Year	1996
Description	Author affiliation: Dept. of Chem. Eng., Univ. of Manchester Inst. of Sci. & Technol., UK (Zimmermann, W.B.J.)
Abstract	The design of a control system to monitor the washing of coal by a froth flotation mechanism is considered. The froth in a batch cell, due to steady sparging by air, reaches an equilibrium height h. This height is determined by the cumulative effects of several resistance mechanisms dissipating the air pressure gradient: viscous fiction of the rising air and of the falling liquid, the surface tension of bubbles, and the buoyancy forces. This control system is based upon a hydrodynamic model for the resistance and a feedback loop consisting of an image processing system that computes bubble density and size distribution needed by the model. The model hypothesis is that bubble flow is an air flow through a porous medium with an effective resistance coefficient K which depends on the dissipative mechanisms given above. The pressure gradient needed to estimate the froth height is found from Darcy's law when the froth is idealized as a set of vertical tubes, with radius R chosen to be the average bubble size, which varies with vertical position, allowing the air to flow through with an average velocity V/sub m/. The model equation is grad p=K V/sub m//R/sub 0//sup 2/. The cellular neural network (CNN) paradigm was chosen for its ability to process images quickly for use as control system element to compute k and thus infer changes to h by changing the set point for air flow rate or by addition of more liquid or surfactant, which would change the drainage rate or the surface tension.
Starting Page	237
Ending Page	241
File Size	337644
Page Count	5
File Format	PDF
ISBN	078033261X
DOI	10.1109/CNNA.1996.566563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-06-24
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Control systems Surface tension Cellular neural networks Monitoring Surface resistance Control system synthesis Size control Hydrodynamics Feedback loop Image processing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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