Transactions on Machine Intelligence

Transactions on Machine Intelligence

A Model for Extracting the Velocity Features of Fluid Movement in Flotation Cells of the Shahr-e Babak Copper Complex Using the PIV Method

Document Type : Original Article

Authors
M. Eghbali Fard 1
M. H. Gholizadeh 2
H. Ghayoumizadeh 3
H. Fatehi Marj 2
1 MSc Student, Department of Electrical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
2 Assistant Professor, Department of Electrical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran
3 Assistant Professor of Biomedical Engineering, Vali-e-Asr University of Rafsanjan
10.47176/TMI.2018.182
Abstract
In this study, the flotation process is examined as a conventional method for processing low-grade copper sulfide ores. The performance of this process is influenced by various factors, including the type and dosage of collector, frother, pH regulator, activator, and depressant. Identifying effective reagents and determining optimal conditions are crucial for enhancing efficiency, and modeling and simulation of this process can further aid in its improvement. Traditionally, experienced operators assess and control the process based on the visual characteristics of the froth. However, with advancements in technology, machine vision has emerged as a valuable tool for monitoring and controlling flotation circuits. In this context, a machine vision system was installed on a flotation cell in the rougher circuit of the Shahr-e Babak Copper Flotation Plant to monitor the process under various conditions. The primary visual feature extracted from the captured images is the bubble velocity on the froth surface, which directly impacts flotation performance. In this research, the Particle Image Velocimetry (PIV) technique was employed to determine bubble velocities without the need for additional particles or lasers. Simulation results demonstrate that the proposed method exhibits high accuracy in providing relevant velocity features, making it a potent tool for monitoring and optimizing the performance of flotation cells.
Keywords
Flotation
Shahr-e Babak
Image Processing
PIV
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Transactions on Machine Intelligence
Volume 1, Issue 4
Autumn 2018
Pages 182-190

  • Receive Date 06 April 2018
  • Revise Date 12 June 2018
  • Accept Date 25 September 2018