The full text of this article
Study of process dynamics in Floatex density separator based on computational intelligent vision
by S.K. Mandal
International Journal of Computational Vision and Robotics (IJCVR), Vol. 2, No. 4, 2011
Abstract: This paper proposes a novel computational intelligent vision-based image processing and analysis techniques that can be used in Floatex density separator (FDS), a hindered settling classifier for recovery of quality products from minerals (iron, coal) in order to develop an optimum process control strategy suitable for manipulating complex variables characterised by relatively slow process dynamics. Image processing and analysis software, MATLAB 7.0 was used to process the high speed CCD camera image. The steps include calibration, contrast enhancement and segmentation. Image features are demonstrated and correlated with voidage, particle size distribution, bed height change and density mapping under specific feed rate, pulp density and teeter flow rate of the process. All these information are used for estimation of bed pressure, underflow density cut which will help in the development of accurate control system for reliable operation of FDS from a remote control station.
Online publication date: Mon, 30-Jan-2012
is only available to individual subscribers or to users at subscribing institutions.
Go to Inderscience Online Journals to access the Full Text of this article.
Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.
Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Vision and Robotics (IJCVR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable).
See our Orders page to subscribe.
If you still need assistance, please email email@example.com