UPM Institutional Repository

Automatic control of flotation process using computer vision


Saravani, Ali Jahed (2015) Automatic control of flotation process using computer vision. PhD thesis, Universiti Putra Malaysia.


In the mineral production industry, the separation of valuable material from waste material is generally carried out using the flotation process. Metallurgical parameters of the process reflect the quality and quantity of the product. Online measurement and control of these parameters is currently not possible, due to lack of scientific relationship between froth structure and various aspects of flotation process. Bubble size distribution which is regarded as the most important characteristics of froth structure, is being addressed in this thesis by using a segmentation algorithm. A marker based watershed algorithm had been adopted and improved so as to prevent the over segmentation of big bubbles and able to adapt itself with different scenario of froth images. This results in a measurement of bubble size with high precision. The performance of improved marker based watershed algorithm was validated by using several industrial and laboratory froth images. In addition, several algorithms were implemented to measure the other important image variables such as froth velocity,froth color and bubble collapse rate. A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. A control strategy based on froth model was then designed in order to optimize the visual characteristics of froth, which lead to the control of the metallurgical parameters in an indirect manner. Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. Simulation results indicated the effective performance of the designed control schemes in enhancing theM overall efficiency of the process.

Download File

FK 2015 76RR.pdf

Download (1MB) | Preview

Additional Metadata

Item Type: Thesis (PhD)
Subject: Flotation - Computer vision
Call Number: FK 2015 76
Chairman Supervisor: Mohammad Hamiruce Marhaban, PhD
Divisions: Faculty of Engineering
Depositing User: Haridan Mohd Jais
Date Deposited: 04 Oct 2017 09:06
Last Modified: 04 Oct 2017 09:06
URI: http://psasir.upm.edu.my/id/eprint/57585
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item