The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems

Abstract

Within froth flotation, it is widely acknowledged that froth stability affects flotation performance.

As a result, it is expected that through the effective management of froth stability, it

would be possible to both control and optimise a flotation cell and bank. However, for this to

be possible, the relationships between the operating conditions, froth stability behaviour and

flotation performance attributes need to be well understood. In addition, froth stability would

need to be measured using a robust method suitable for on-line operation.

Within the literature, no robust methods are available to measure either the concentration of

solids on the froth surface, or froth stability in a manner suitable for on-line operation. Thus,

two novel non-intrusive machine vision measurements have been developed in this work to

quantify these attributes. A measure for the solids loading on the froth surface was developed

by measuring the roughness or texture of the segmented images of individual bubbles. A

burst rate measurement was developed by identifying bursting bubbles on the froth surface

through the comparison of consecutive segmented images. It was also shown that the burst

rate could be used to obtain a measure of the air loss rate from the froth surface. The burst

rate measurement is considered to relate directly to froth stability. The validity of the machine

vision measurements were tested by comparing the effect of an operating condition on the

machine vision measurement with the expected effect, based upon previous findings from the

literature.

Froth stability encompasses a number of mechanisms, such as bubble coalescence causing

an increase in bubble size, loss of interfacial surface area, detachment of particles, release of

water and promotion of drainage. It is expected that operating variables will affect each of

these factors differently, resulting in complex and inconsistent stability behaviour. Currently,

no model exists that adequately describes the three-phase froth stability behaviour in terms of

the effect of operating variables and internal mechanisms that occur within a froth.

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APA

Morar, S (2021). The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems. Afribary. Retrieved from https://afribary.com/works/the-use-of-machine-vision-to-describe-and-evaluate-froth-phase-behaviour-and-performance-in-mineral-flotation-systems

MLA 8th

Morar, Sameer "The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems" Afribary. Afribary, 15 May. 2021, https://afribary.com/works/the-use-of-machine-vision-to-describe-and-evaluate-froth-phase-behaviour-and-performance-in-mineral-flotation-systems. Accessed 12 May. 2024.

MLA7

Morar, Sameer . "The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems". Afribary, Afribary, 15 May. 2021. Web. 12 May. 2024. < https://afribary.com/works/the-use-of-machine-vision-to-describe-and-evaluate-froth-phase-behaviour-and-performance-in-mineral-flotation-systems >.

Chicago

Morar, Sameer . "The use of machine vision to describe and evaluate froth phase behaviour and performance in mineral flotation systems" Afribary (2021). Accessed May 12, 2024. https://afribary.com/works/the-use-of-machine-vision-to-describe-and-evaluate-froth-phase-behaviour-and-performance-in-mineral-flotation-systems