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Development of a machine vision system for real-time monitoring and control of batch flotation process

Substantial progresses have been made over the past decade in using machine vision for automatic control of the froth flotation process. A machine vision system is able to extract the visual features from the captured froth images and present the results to process control systems. The current resea...

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Main Authors: Jahedsaravani, Ali, Massinaei, Mohammad, Marhaban, Mohammad Hamiruce
Format: Article
Language:English
Published: Elsevier 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61445/1/Development%20of%20a%20machine%20vision%20system%20for%20real-time%20monitoring%20and%20control%20of%20batch%20flotation%20process.pdf
http://psasir.upm.edu.my/id/eprint/61445/
https://www.sciencedirect.com/science/article/pii/S0301751617301564
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spelling my.upm.eprints.614452018-05-24T03:03:32Z http://psasir.upm.edu.my/id/eprint/61445/ Development of a machine vision system for real-time monitoring and control of batch flotation process Jahedsaravani, Ali Massinaei, Mohammad Marhaban, Mohammad Hamiruce Substantial progresses have been made over the past decade in using machine vision for automatic control of the froth flotation process. A machine vision system is able to extract the visual features from the captured froth images and present the results to process control systems. The current research work is concerned with the development and implementation of a machine vision system for real time monitoring and control of a batch flotation system. The proposed model-based control system comprises two in-series models connecting the process variables to the froth features and the metallurgical parameters along with a stabilizing fuzzy controller. The results indicate the developed machine vision based control system is able to accurately predict the metallurgical parameters of the existing batch flotation system from the extracted froth features and efficiently maintain them at their set-points despite step disturbances in the process variables. Furthermore, the proposed control system leads to higher target values for the metallurgical parameters than the previously developed system (RCu = 91.1 % ; GCu = 11.2% vs. RCu = 87.6 % ; GCu = 8.1%). Elsevier 2017-10 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61445/1/Development%20of%20a%20machine%20vision%20system%20for%20real-time%20monitoring%20and%20control%20of%20batch%20flotation%20process.pdf Jahedsaravani, Ali and Massinaei, Mohammad and Marhaban, Mohammad Hamiruce (2017) Development of a machine vision system for real-time monitoring and control of batch flotation process. International Journal of Mineral Processing, 167. 16 - 26. ISSN 0301-7516 https://www.sciencedirect.com/science/article/pii/S0301751617301564 10.1016/j.minpro.2017.07.011
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Substantial progresses have been made over the past decade in using machine vision for automatic control of the froth flotation process. A machine vision system is able to extract the visual features from the captured froth images and present the results to process control systems. The current research work is concerned with the development and implementation of a machine vision system for real time monitoring and control of a batch flotation system. The proposed model-based control system comprises two in-series models connecting the process variables to the froth features and the metallurgical parameters along with a stabilizing fuzzy controller. The results indicate the developed machine vision based control system is able to accurately predict the metallurgical parameters of the existing batch flotation system from the extracted froth features and efficiently maintain them at their set-points despite step disturbances in the process variables. Furthermore, the proposed control system leads to higher target values for the metallurgical parameters than the previously developed system (RCu = 91.1 % ; GCu = 11.2% vs. RCu = 87.6 % ; GCu = 8.1%).
format Article
author Jahedsaravani, Ali
Massinaei, Mohammad
Marhaban, Mohammad Hamiruce
spellingShingle Jahedsaravani, Ali
Massinaei, Mohammad
Marhaban, Mohammad Hamiruce
Development of a machine vision system for real-time monitoring and control of batch flotation process
author_facet Jahedsaravani, Ali
Massinaei, Mohammad
Marhaban, Mohammad Hamiruce
author_sort Jahedsaravani, Ali
title Development of a machine vision system for real-time monitoring and control of batch flotation process
title_short Development of a machine vision system for real-time monitoring and control of batch flotation process
title_full Development of a machine vision system for real-time monitoring and control of batch flotation process
title_fullStr Development of a machine vision system for real-time monitoring and control of batch flotation process
title_full_unstemmed Development of a machine vision system for real-time monitoring and control of batch flotation process
title_sort development of a machine vision system for real-time monitoring and control of batch flotation process
publisher Elsevier
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61445/1/Development%20of%20a%20machine%20vision%20system%20for%20real-time%20monitoring%20and%20control%20of%20batch%20flotation%20process.pdf
http://psasir.upm.edu.my/id/eprint/61445/
https://www.sciencedirect.com/science/article/pii/S0301751617301564
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score 13.211869

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