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

fYear

2013

fDate

6-8 March 2013

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition and Image Analysis (PRIA), 2013 First Iranian Conference on

Conference_Location

Birjand

Print_ISBN

978-1-4673-6204-7

Type

conf

DOI

10.1109/PRIA.2013.6528458

Filename

6528458