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European Journal of Applied Sciences – Vol. 11, No. 2
Publication Date: April 25, 2023
DOI:10.14738/aivp.112.14527.
Leiva, C. A., Borjas, J., Acuña, C., & Luukkanen, S. (2023). Applied Online Bubble Size Distribution Measurement in a Pilot Flotation
Cell Based on Image Analysis. European Journal of Applied Sciences, Vol - 11(2). 645-662.
Services for Science and Education – United Kingdom
Applied Online Bubble Size Distribution Measurement in a Pilot
Flotation Cell Based on Image Analysis
C.A. Leiva
Oulu Mining School, University of Oulu, Oulu,
Finland and Departamento de Ingeniería Química,
Universidad Católica del Norte, Antofagasta, Chile
José Borjas
Departamento de Ingeniería Química,
Universidad Católica del Norte, Antofagasta, Chile
Claudio Acuña
Department of Chemical and Environmental Engineering,
Universidad Técnica Federico Santa María, Valparaíso, Chile
Saija Luukkanen
Oulu Mining School, University of Oulu, Oulu, Finland
ABSTRACT
The distribution of bubble size in the pulp is a parameter directly related to the
flotation kinetics, but its measurement is complex to determine due to the presence
of particles and cluster of bubbles. The existing equipment for the measurement of
bubble size (McGill and UCT), which operate manually and batch, requires
specialized operators in image analysis. On the other hand, the McGill technique has
not been directly validated with bubble swarms and only 10% of the sampled
bubbles are analyzed. These aspects have limited the technology transfer and
sustainability in the measurement of bubble size. To solve the problems presented,
a device based on the McGill technique was designed and implemented.
Furthermore, algorithms were implemented to increase the statistical significance
of the measurement of bubbles per image. The validation consisted of a comparison
of the degree of detection using the software manually and automatically
(undetected remaining bubbles). As a result, it is possible to predict the bubble size
distributions with an error of less than 5% and derivations close to 0.1 [mm] in the
determination of D32, using an average of 100 images. In conclusion, the new device
and algorithms improve the accuracy of BSD measurements, helping to optimize the
process, predict, control flotation kinetics, and be used as a troubleshooting tool.
The new device and algorithms improve the accuracy of BSD measurements,
helping to optimize the process, predict, control flotation kinetics, and be used as a
troubleshooting tool.
Keywords: Bubbles, Flotation; Image Analysis
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Services for Science and Education – United Kingdom 646
European Journal of Applied Sciences (EJAS) Vol. 11, Issue 2, April-2023
INTRODUCTION
The mineral concentration process is carried out, to a large extent, by froth flotation. Flotation
consists in the separation of the valuable mineral particles contained in solid-liquid dispersion
(pulp) by means of their selective adhesion to air bubbles, which float and concentrate in the
form of froth. The efficiency of this process depends on the physicochemical aspect in particle- bubble adhesion [1], characteristics of the circuit [2] and the hydrodynamics of the equipment
in the collection area (dispersion of gas in the pulp) [3], which includes gas superficial velocity
(Jg), gas volume fraction (Eg), size distribution (BSD) and bubble stability, being the bubble size
distribution the parameter that directly affects the kinetics of the process [4]. Nevertheless,
only few techniques have been developed to determine this parameter, in which they can
operate both on a laboratory scale and in industrial plants. Furthermore, studies about the
validation of these techniques are scarce in the literature [5].
The measurement of bubble size is one of the most complex aspects to determine due to the
presence of heterogeneous mixtures in the cells (water, dark particles, single bubbles and
swarms of bubbles) [6] and it has been studied by various researchers [7, 8], reaching a great
level of sophistication in the development of non-invasive techniques [9-11] including:
ultrasound [12], radiography and tomography imaging, nuclear magnetic resonance imaging
(NMR) and velocimetric techniques (Laser Doppler Anemometer (LDA), Particle Image
Velocimetry (PIV), [13]). However, these techniques are substantively complex to be
implemented at an industrial level, although there are some methods that use image analysis
[14, 15]. Only two methods have been used at this level and these are the following: an imaging
sample tracking technique [16] and a capillary technique [17]. The analysis of the bubble size
distribution has been extensively studied [18-26], being a basis for achieving the most accurate
data collection possible.
The current bubble size measurement is built on models based on one-way flow or “drift flux”
analysis. Likewise, the model has been extended to be adapted for bubble swarms, thus relating,
the distribution of bubble size (db) with the superficial gas velocity (Jg), superficial liquid
velocity (Ji) and hold-up gas (Eg), being contrasted with photographic measurements. Several
study mechanisms have been identified on the bubble size distribution, among which the McGill
Bubble Viewer device is the most widely used technique to determine the bubble size
distribution [27-37].
Because of these reasons, a compact continuous measurement device is designed and
evaluated, which allows the detection of bubble size distribution in cells at the laboratory level.
The device continuously measures through a regulated vacuum system, allowing incoming air
to be removed and the liquid level maintained.
The bubble detection has been enhanced with algorithms that allow discriminating the bubbles
from swarms, differentiate irregular bubbles, and isolate bubbles in areas of irregular lighting.
As detection algorithms, it was proposed to use the quotient between the convex area and the
projected area of the isolated segment and a variable threshold to separate bubbles into
swarms and illumination zones. To validate the algorithms and the continuous measurement
system, the device was implemented in a pilot cell with a controlled bubble size distribution