A Comprehensive Review of Froth Surface Monitoring as an Aid for Grade and Recovery Prediction of Flotation Process. Part B: Texture and Dynamic Features

Abstract

In the last few decades, many studies have been performed with the main hope of utilizing imaging methods so as to detect static (bubble size and shape, color, texture) and dynamic (velocity and stability) features of froth that involve crucial information about the process state in order to assess and monitor the performance of flotation process. Although several types of flotation automated control system problems are being successfully solved using the various techniques of features extraction from froth images, there are still a number of unresolved subjects and obstacles. Hence, a suitable review of these methods is needed. After reviewing the technical aspects of froth images structural features in part 1 of this two-part review paper, this work provides an overview of several different approaches for the sake of analyzing and classifying froth image texture and dynamic features. Finally, we conclude our review by linking concentrate grade and recovery with the froth image features described in this two-part paper. In the close future, it is expected with ever-growing application needs and research progress, image analysis systems are becoming even more effective solutions for monitoring and controlling flotation performance. This review provides a platform for future initiatives and potential developments in this area.

Department(s)

Mining Engineering

Keywords and Phrases

Froth flotation; Grade; Image analysis; recovery; Texture and dynamic features

International Standard Serial Number (ISSN)

1556-7230; 1556-7036

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Taylor and Francis Group; Taylor and Francis, All rights reserved.

Publication Date

01 Jan 2023

Link to Full Text

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