Title :
Image processing-based monitoring of a batch flotation process
Author :
Massinaei, M. ; Mehrshad, N. ; Hosseini, M.R.
Author_Institution :
Dept. of Min. Eng. & Electr. & Comput. Eng. Respectively, Univ. of Birjand, Birjand, Iran
Abstract :
Machine vision technology now offers a viable means of monitoring and controlling flotation performance. In this study an image analysis algorithm utilizing an adaptive marker based watershed transform was developed to segment the froth images and measure the bubble size over a wide range of process conditions. Flotation experiments were conducted at a wide range of operating conditions (i.e. gas flow rate, slurry solids %, frother dosage and collector dosage) and the froth mean bubble size was determined for each run. The results showed that the proposed algorithm can be successfully applied to monitor the flotation process at different conditions.
Keywords :
bubbles; computer vision; flotation (process); image segmentation; process monitoring; production engineering computing; slurries; transforms; adaptive marker based watershed transform; batch flotation process; bubble size measurement; collector dosage; flotation experiment; flotation performance control; flotation performance monitoring; froth image segmentation; froth mean bubble size; frother dosage; gas flow rate; image analysis algorithm; image processing-based monitoring; machine vision technology; operating condition; process condition; slurry solid; Algorithm design and analysis; Fluid flow; Image segmentation; Minerals; Monitoring; Size measurement; Slurries; Bubble size; Froth Flotation; Image analysis; Neural network;
Conference_Titel :
Pattern Recognition and Image Analysis (PRIA), 2013 First Iranian Conference on
Conference_Location :
Birjand
Print_ISBN :
978-1-4673-6204-7
DOI :
10.1109/PRIA.2013.6528458
