=Paper=
{{Paper
|id=Vol-2853/paper49
|storemode=property
|title=The Cyber-Physical System for Increasing the Efficiency of the Iron Ore Desliming Process
|pdfUrl=https://ceur-ws.org/Vol-2853/paper49.pdf
|volume=Vol-2853
|authors=Volodymyr Morkun,Natalia Morkun,Andrii Pikilnyak,Serhii Semerikov,Oleksandra Serdiuk,Irina Gaponenko
|dblpUrl=https://dblp.org/rec/conf/intelitsis/MorkunMPSSG21
}}
==The Cyber-Physical System for Increasing the Efficiency of the Iron Ore Desliming Process==
https://ceur-ws.org/Vol-2853/paper49.pdf
The Cyber-Physical System for Increasing the Efficiency of the
Iron Ore Desliming Process
Volodymyr Morkuna, Natalia Morkuna, Andrii Pikilnyaka, Serhii Semerikovb, Oleksandra
Serdiuka, Irina Gaponenkoa
a
Kryvyi Rih National University, Vitaly Matusevich str, 11, Kryvyi Rih, 50027, Ukraine
b
Kryvyi Rih State Pedagogical University, Gagarin av. 54, Kryvyi Rih, 50086, Ukraine
Abstract
It is proposed to carry out the spatial effect of high-energy ultrasound dynamic effects with
controlled characteristics on the solid phase particles of the ore pulp in the deslimer input
product to increase the efficiency of thickening and desliming processes of iron ore
beneficiation products. The above allows predicting the characteristics of particle
gravitational sedimentation based on an assessment of the spatial dynamics of pulp solid-
phase particles under the controlled action of high-energy ultrasound and fuzzy logical
inference. The object of study is the assessment of the characteristics and the process of
control the operations of thickening and deslaming of iron ore beneficiation products in the
conditions of the technological line of the ore beneficiation plant. The subject of study is a
cyber-physical system based on the use of high-energy ultrasound radiation pressure effects
on iron-containing beneficiation products in the technological processes of thickening and
desliming. The working hypothesis of the project is that there is a relationship between the
physical-mechanical and chemical-mineralogical characteristics of the iron ore pulp solid-
phase particles and their behavior in technological flows under the influence of controlled
ultrasonic radiation, based on which the imitation modeling of the gravitational sedimentation
process of the iron ore pulp solid-phase particles can be performed directly in the
technological process. Also, the optimal control actions concerning the processes of
thickening and desliming can be determined.
Keywords 1
Cyber-physical system, simulation, ultrasound, gamma radiation, fuzzy inference, deslimer
1. Introduction
An important element in the chain of the technological process of iron ore concentrate obtaining at
mining and processing plants is gravity hydraulic beneficiation in deslimers. The use of deslimers,
depending on the stage of beneficiation, allows increasing the mass fraction of total iron in the
thickened product by 0.5-3.5%. It is possible to reduce the negative impact of variable characteristics
of ore on the productivity and energy consumption of technological complexes of the processing plant
only if there is operational information on the main characteristics of raw materials and processing
products, which can be obtained by analyzing the behaviour of pulp solid-phase particles under the
action of high-energy ultrasound. Therefore, the development of methods and tools aimed at
improving the efficiency of the processes of thickening and desliming of iron ore beneficiation
products based on the use of ultrasonic effects is an urgent scientific problem.
IntelITSIS’2021: 2nd International Workshop on Intelligent Information Technologies and Systems of Information Security, March 24–26,
2021, Khmelnytskyi, Ukraine
EMAIL: morkunv@gmail.com (V. Morkun); nmorkun@gmail.com (N. Morkun); pikilnyak@gmail.com (A. Pikilnyak);
semerikov@gmail.com (S. Semerikov); o.serdiuk@i.ua (O. Serdiuk); gaponenko@gmail.com (I. Gaponenko)
ORCID: 0000-0003-1506-9759 (V. Morkun); 0000-0002-1261-1170 (N. Morkun); 0000-0003-0898-4756 (A. Pikilnyak); 0000-0003-0789-
0272 (S. Semerikov);0000-0001-5629-0279 (O. Serdiuk); 0000-0002-0339-4581 (I. Gaponenko)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
2. Related Works.
In [1] the flocculation of iron ore raw materials in deslimers at an ore processing plant is
investigated. The dependences of the flocculation efficiency (sedimentation rate, turbidity and
sediment volume) on the flocculant dose were obtained. At the same time, the disadvantage of this
approach is the use of chemical action, which complicates the operational control of the processes of
thickening and desliming. In [2], the dependences of the increase in the residence time of solid-phase
particles due to the depth of the sediment layer and due to the sediment flow are presented. The
efficiency indicators of the thickening process are calculated. At the same time, the disadvantage is
that the work does not offer methods of operational control of the characteristics of ore particles, in
particular their size. The study results of the dehydration process for suspension, the solid phase of
which consists mainly of ultrafine particles, are presented in [3]. In this approach, the issue of the
control action formation directly in the course of the technological process to increase the efficiency
of thickening processes is considered. In [4] methods of computational fluid dynamics were used to
optimize the design and performance of thickening operations. The authors used the particle number
balance model. The approach requires additional research to form the information support of the
operational data control system for the distribution of particles in the thickener and their physical-
mechanical and chemical-mineralogical characteristics. In [5] it was proved that at the concentration
of the flocculant solution the concentration of sands with and without a shift differs significantly. To
apply the presented dependencies when controlling the processes of thickening and desliming, it is
necessary to consider the differences in the characteristics of individual mineralogical and
technological varieties of ore material, as well as surface contamination of ore particles. The
processes of removing highly dispersed suspended solids from process water during the iron ore
beneficiation were studied in [6]. The disadvantage of this approach is the use of chemical action on
the processes of thickening and desliming, which complicates the operational control of the processes.
In [7], an evolutionary algorithm for the synthesis of a neural network model using data collected
from an ore-processing plant was proposed. This approach requires additional research to form the
information support of the optimization system for beneficiation processes with operational data on
their parameters. The work [8, 9] presents the results of systematic studies on the characteristics of
flocculation, sedimentation and consolidation of ore tailings using different polyacrylamide
flocculants. The same disadvantage as in the above-mentioned approach is the use of chemical action
on the processes of thickening and desliming, which complicates the operational control of the
processes. In work [10], the influence of the characteristics of ultrasonic radiation: frequency, power,
exposure time (5-20 min) on the final concentration of thickener sands and flocculation processes in
this unit is considered. It has been found that ultrasound can significantly improve the concentration
of the discharge, and its frequency and power are the most important factors of influence. In [11, 12],
the processes of processing a suspension using ultrasound and its effect on electrochemical and
flocculation processes to increase the efficiency of deposition processes were studied. However, the
application of the above methods of ultrasonic exposure to the processes of thickening in the
processing of several mineral and technological varieties of ore requires additional research [13-15].
3. Proposed methodology
The idea of the method is that increasing the efficiency of thickening and deslaming processes of
iron ore beneficiation products can be achieved by the spatial influence of dynamic effects of high-
energy ultrasound with controlled characteristics on the ore pulp solid-phase particles in the deslimer
input product. This allows us to predict the characteristics of their gravitational deposition based on
the assessment of the spatial dynamics of the pulp solid-phase particles under the controlled action of
high-energy ultrasound and fuzzy logic inference [16-18].
Let’s evaluate the effect of ultrasonic radiation pressure on the change in the concentration of
particles with radius r. Let the pulp with the velocity of V flow in the positive direction of the X-axis.
Let’s denote by nr(Z,t) the concentration of the particles of radius r at the depth Z at the moment of t.
Considering the work [19-21] the equation will look as follows
𝜕𝜕𝑛𝑛𝑟𝑟 (𝑍𝑍,𝑡𝑡) 𝜕𝜕
= − [𝑉𝑉𝑟𝑟 (𝑍𝑍, 𝑡𝑡)𝑛𝑛𝑟𝑟 (𝑍𝑍, 𝑡𝑡)] . (1)
𝜕𝜕𝜕𝜕 𝜕𝜕𝜕𝜕
where 𝑉𝑉𝑟𝑟 (𝑍𝑍, 𝑡𝑡) – is the velocity of the particle displacement of radius r, and the coordinate Z in the
ultrasound field. The velocity is directed along the Z-axis, that is, it is perpendicular to the pulp flow.
Assuming that the intensity of the ultrasonic wave I varies exponentially (the initial value), its
attenuation coefficient α depends on a sound frequency νo and taking to account the analysis of works
[20, 22], the particle concentration nr(Z,t) is determined as follows
𝑒𝑒 𝛼𝛼 𝑧𝑧
𝑛𝑛𝑟𝑟 (𝑍𝑍, 𝑡𝑡) = 𝑛𝑛0 𝑒𝑒 𝛼𝛼 𝑧𝑧−𝛼𝛼𝛼𝛼𝛼𝛼 𝑆𝑆𝑆𝑆(𝑒𝑒 𝛼𝛼 𝑧𝑧 − 1 − 𝛼𝛼𝛼𝛼𝛼𝛼), (2)
0, 𝑋𝑋<0
where 𝑛𝑛𝑟𝑟 (𝑍𝑍, 0) = 𝑛𝑛0 , 𝑛𝑛𝑟𝑟 (0, 𝑡𝑡) = 0 - are the initial and boundary conditions; 𝑆𝑆𝑆𝑆(𝑋𝑋) = � ;
1, X ≥ 0
2𝑟𝑟(𝑘𝑘𝑘𝑘)4 2 3 2 𝑟𝑟𝑐𝑐 2 𝜌𝜌 −𝜌𝜌
𝛽𝛽 =
27𝜂𝜂𝜂𝜂
𝐼𝐼0 (𝑎𝑎1 + 𝑎𝑎1 𝑎𝑎2 + 𝑎𝑎2 ); 𝑎𝑎1 = 1 − 𝜌𝜌𝑠𝑠 𝑐𝑐𝑠𝑠2
; а2 = 2 𝑠𝑠 +𝜌𝜌 ; ρs, cs – are the particle density and
4 2𝜌𝜌𝑠𝑠
ultrasound speed in particle material; ρ, с – the density of the medium under study and the speed of
ultrasound in it.
The calculation of the high-energy ultrasound power, which allows the predicted displacement of
particles of crushed ore of a certain mass in the pulp flow, was carried out based on the results
obtained from the study of the ultrasonic pulse front propagation using a HIFU Simulator v1.2 [23]
(Figure 1).
Figure 1: The ultrasonic power along the z-axis.
All grain sizes of the crushed material can be shifted under the increase in the high-energy
ultrasound intensity Ih from zero to a specific value and a constant flow rate of pulp in the zone of
measurement, sequentially [20, 24, 25]
𝑑𝑑
𝛾𝛾𝑖𝑖 = ∫𝑑𝑑 𝑖𝑖+1 𝛾𝛾(𝑑𝑑)𝑑𝑑𝑑𝑑. (3)
𝑖𝑖
In this case, the average content of the useful component in this fraction is equal to
−1 𝑑𝑑
𝛽𝛽𝑖𝑖 = 𝛾𝛾𝑖𝑖 ∫𝑑𝑑 𝑖𝑖+1 𝛽𝛽(𝑑𝑑)𝛾𝛾(𝑑𝑑)𝑑𝑑𝑑𝑑. (4)
𝑖𝑖
The concentration of the pulp solid phase in the measurement zone is determined using ultrasonic
measurements and the density of its particles using gamma radiation in the radiometric measuring
channel.
A signal 𝑆𝑆𝛾𝛾 is generated in the radiometric channel based on measurements of the gamma radiation
attenuation in water Iw and pulp Ip
𝑆𝑆𝛾𝛾 = 𝑙𝑙𝑙𝑙( 𝐼𝐼𝑤𝑤 /𝐼𝐼𝑝𝑝 ) = 𝐴𝐴𝐴𝐴[(𝜌𝜌𝑠𝑠 𝜇𝜇𝑠𝑠 − 𝜌𝜌𝑤𝑤 𝜇𝜇𝑤𝑤 )𝑙𝑙], (5)
where A – is the coefficient of proportionality; µw і µs – are the mass attenuation coefficients of water
and ore pulp material; ρw and ρs – density of water and particles of ore pulp material, kg/m3; W – is
the ore particle volume fraction in the pulp.
The low-frequency ultrasonic waves were used for measurements of the pulp solid phase
concentration. As shown in [20, 23, 26], the amplitude of the ultrasonic wave with frequency ν, which
passed in the pulp distance z, can be described as follows
𝑧𝑧𝑧𝑧 𝑟𝑟𝑚𝑚
𝐴𝐴𝜈𝜈 (𝑧𝑧) = 𝐴𝐴𝑤𝑤 𝑒𝑒𝑒𝑒𝑒𝑒 �− ∫ 𝜎𝜎(𝑣𝑣, 𝑟𝑟)𝑓𝑓(𝑟𝑟)𝑑𝑑�, (6)
𝑉𝑉 0
where n - the number of particles in the effective control volume of the pulp; АВ – is the amplitude of
the wave passing the distance z in pure water; rm - the maximum size of solid particles; σ(v,r) – is the
total attenuation coefficient of ultrasound on a particle of radius r.
The value σ(v,r) is determined by the sum of the coefficients of ultrasound absorption and
scattering
𝜎𝜎(𝑣𝑣, 𝑟𝑟) = 𝜎𝜎𝑐𝑐 (𝑣𝑣, 𝑟𝑟) + 𝜎𝜎𝑠𝑠 (𝜈𝜈, 𝑟𝑟) (7)
The graphs of the dependences of the ultrasonic wave attenuation α on the frequency, which
obtained using the software package k-Wave Toolbox are presented in Figure 2. The value of y
determines the acoustic density of the medium.
Figure 2: The dependences of the ultrasonic wave attenuation α on frequency during propagation in
a homogeneous medium
In the region of low-frequency (ν ≤ 106 Hz) the ultrasound attenuation is mainly due to viscous
inertial losses, so the ultrasound attenuation cross-section σc at this frequency ν1 is determined only
by the pulp solid phase concentration W and doesn’t depend on the ore particle size distribution F(r).
The signal S1 is obtained from measurements of the amplitude of the ultrasonic wavesthat have passed
the distance z in water А01 and pulp А𝜈𝜈1 determines the pulp solid phase concentration
𝑊𝑊𝑊𝑊 𝑟𝑟𝑚𝑚
𝑆𝑆1 = 𝑙𝑙𝑙𝑙( А01 /А𝜈𝜈1 ) = ∫ 𝜎𝜎(𝑣𝑣1 , 𝑟𝑟) 𝐹𝐹(𝑟𝑟)𝑑𝑑𝑑𝑑, (8)
ℵ 0
In this expression
𝑟𝑟
ℵ = 4/3πr3 ∫𝑜𝑜 𝑚𝑚 𝐹𝐹(𝑟𝑟)dr. (9)
The ratio of Sγ (5) and S1 (8) depends only on the density of the pulp solid phase particles in the
zone of measurements and determines the useful component content in certain grades of particle size
of crushed ore
𝑆𝑆
𝑆𝑆4 = 𝐵𝐵 𝑆𝑆𝛾𝛾, (10)
1
where В – is the coefficient of proportionality; Sγ – is the signal that depends on the concentration and
density of solid-phase particles; S1 – is the signal proportional to the solid phase concentration in the
pulp.
The use of a measuring channel based on high-frequency ultrasonic waves [20, 21, 28] allows the
measurement of the size control class content of the crushed ore. In the high-frequency range, with σ
(ν2,r) ≈ σs, the value
𝑟𝑟 Z W 𝑟𝑟
S2 = ln(А02 /А𝜈𝜈2 ) =Z2N∫𝑜𝑜 𝑚𝑚 𝐹𝐹(𝑟𝑟)𝜎𝜎𝑠𝑠 (𝜈𝜈1 , 𝑟𝑟) = 2 ∫𝑜𝑜 𝑚𝑚 𝐹𝐹(𝑟𝑟)𝜎𝜎𝑠𝑠 (𝜈𝜈2 , 𝑟𝑟) dr (11)
ℵ
is measured. Then the ratio
𝑆𝑆3 = 𝑆𝑆2 /𝑆𝑆1 (12)
doesn’t depend on the pulp solid-phase concentration and is determined only by the concentration of
the ore particle size control class [20, 21].
The cyber-physical system and program for modelling the crushed ore fraction redistribution in the
ore pulp under the influence of the high-energy ultrasound radiation pressure according to the above
expressions were developed. The program main window is shown in Figure 3. The program allows to
vary the crushed ore particle density in the specified size ranges. The geometry of the measurements,
the position of the source and the ultrasonic vibration intensity, the concentration of solid-phase
particles and their size distribution before the simulation are set.
Figure 3: Redistribution of crushed ore particles in the pulp under the influence of high-energy
ultrasound
The simulated measurement area is represented by a measuring container. The length and diameter
of the container can be changed and is directly related to the strength of the ultrasound radiation
pressure, which is determined by the intensity of ultrasound radiation generated by the emitter
(source). The measurement range is the number (set) of sections of the measurement zone in which
the number of particles falling into them is counted. The ordinate axis (Figure 3) displays the number
of processed particles, and the output scale automatically expands as the simulation time increases,
i.e. the number of passing particles.
The proposed method for evaluating the distribution function of the useful component by size
classes of crushed ore particles in a pulp flow, which based on measurements of the parameters of the
propagation of high-frequency and low-frequency ultrasonic waves, as well as gamma radiation,
differs from the existing ones in that during the measurements, the crushed ore particles of a certain
size and density are displaced into the measurement area by exposing the pulp to high-energy
ultrasound. The obtained results make it possible to predict the distribution of the iron ore solid phase
in terms of size and density (the content of the useful component) in the deslimer initial product and
to form control actions on this basis.
4. Results
Practical approbation of the developed theoretical, algorithmic and program-technical decisions
was carried out on experimental-industrial installations, experimental and production base of the
enterprises of Association "Ukrrudprom" and "Rudpromgeofizika". The technical means of ultrasonic
and radiometric control were connected to a computer using a high-precision 24-bit analogue-to-
digital converter ZET 230 via a USB 2.0 interface [29]. The conversion frequency on each channel of
the ZET 230 module is up to 100 kHz, the maximum input voltage is ± 10 V, the supported exchange
rates are from 75 to 115200 bps. In a frequency range of 10 Hz ... 20 kHz and a dynamic range of 100
dB, the maximum unevenness of the amplitude-frequency characteristic of the ZET 230 module is 1
dB.
The evaluation of the crushed ore particle distribution function by size and density (the useful
component content) was carried out by evaluating their redistribution in the pulp flow under the
influence of radiation pressure of high-energy ultrasound. In this case, the intensity of ultrasonic
waves with a frequency of 5 MHz and 1 MHz, as well as gamma radiation transmitted through the
studied medium was determined. The measurement configuration and hardware implementation in
this part of the experiments performed corresponding to the methodology given in [20].
The signal recorded by the ultrasonic granulometer "Pulsar" [20], corresponding to the change in
the particle size in the controlled volume of the pulp under the influence of the radiation pressure of
high-energy ultrasound is shown in Figure 4. In the original undisturbed medium, the density of the
pulp was 1250 g/l, and the content of the class -74 µm was 80%.
Figure 4: The changes in the size of particles in a controlled volume of ore pulp under the influence
of high-energy ultrasound radiation pressure
The identification of the obtained dependencies at the stage of laboratory research was carried out
using the MATLAB 7.0 software [30]. The Fuzzy Logic Toolbox, which is part of the MATLAB
system, contains a set of GUI modules that provide the structural identification stage in an interactive
mode. At this stage, the number of inputs and outputs of the model is determined, the number of terms
and types of accessory functions is set, and the knowledge base is formed.
The knowledge base was formed directly from the results of measurements of S1 according to (8)
(concentration of the pulp solid phase), the value S3 following (12) (concentration of the control class
of the pulp solid phase particle size), the value S4 following (10) (the density of particles of the pulp
solid phase) and the signal corresponding to the current value of the acoustic power radiated into the
pulp flow by the working waveguide.
As the last value, the value of the electric power supplied to the load by the ultrasonic emitter was
used. A three-term lattice partitioning algorithm was used to evaluate each input variable with a
Gaussian membership function. The structure of the model is shown in Figure 5.
The task of the model example was to reproduce the distribution of the useful component by the
size fractions and the granulometric (sieve) characteristics of the deslimer products. The fuzzy model
is optimized for a training set of 1250 numeric input-output arrays. For each of the 25 prepared
samples in the automatic mode, 50 cycles of measurements of the controlled parameters were
performed. The measured values were presented in the standard potential form 0-10 V: acoustic
power signal radiated into the pulp flow by the working waveguide (input1); pulp solids concentration
signal (input2); control signal of the particle size concentration in the pulp solid phase (input3);
particle density signal of the pulp solid phase (input4). The results of training the model are shown in
Figure 6.
Figure 5: Structural diagram of the fuzzy model TS4311
Figure 6: Training results of the TS4311 model
The granulometric (sieve) characteristics of the deslimer discharge and the distribution of iron by
size fractions restored following the simulation results are shown in Figure 7. It also shows a
graphical display of the reconstruction error (for the convenience of analysis of Figure 7, the error
value is doubled). The mean square error of identification of this model on a control sample of 10
points is 2.01.
The performed analysis confirmed the reproducibility of the results obtained. The developed
method and the hardware-software complex that implements it makes it possible to correctly restore
the function of crushed ore particles in terms of size and density, as well as to identify and form a
curve of the separation efficiency of the deslimer based on this function. The resulting dependencies
were used to initialize the hybrid fuzzy model of the deslimer, which was used to assess the state of
the control object and form control actions.
Figure 7: The results of modelling the granulometric characteristics of the deslimer discharge (a) (a
standard set of sieves n = 10 from 44 microns to 1651 microns), as well as the distribution of iron by
size fractions (b).
5. Conclusion
The developed cyber-physical system for evaluating the efficiency of the iron ore desliming
process ensures the formation and maintenance of the necessary characteristics (particle size
distribution and particle density) of iron ore in its discharge by forming control actions based on the
results of ultrasonic and radiometric measurements of pulp parameters and fuzzy inference. This
allows to reduce the operating time of technological units outside their optimal characteristics and
thereby ensures the achievement of the target beneficiation indicators while maximizing productivity
and energy efficiency. The error in restoring the distribution function of crushed material particles in
terms of size and density in the standard deviation is 1.8 - 2.35%.
The results obtained were used in the construction and development of technical and algorithmic
support for ACSs of technological processes at the mining enterprises of the Association
"Ukrrudprom".
6. References
[1] R. Arjmand, M. Massinaei, A. Behnamfard, Improving flocculation and dewatering performance
of iron tailings thickeners, Journal Of Water Process Engineering. 31 (2019) 100873.
doi:10.1016/j.jwpe.2019.100873.
[2] M. Garmsiri, M. Unesi, Challenges and opportunities of hydrocyclone-thickener dewatering
circuit: A pilot scale study, Minerals Engineering. 122 (2018) 206-210.
doi:10.1016/j.mineng.2018.04.001.
[3] S. Tripathy, Y. Murthy, S. Farrokhpay, L. Filippov, Design and analysis of dewatering circuits
for a chromite processing plant tailing slurry, Mineral Processing And Extractive Metallurgy
Review. 42 (2019) 102-114. doi:10.1080/08827508.2019.1700983.
[4] P. Fawell, T. Nguyen, C. Solnordal, D. Stephens, Enhancing Gravity Thickener Feedwell Design
and Operation for Optimal Flocculation through the Application of Computational Fluid
Dynamics, Mineral Processing And Extractive Metallurgy Review. (2019) 1-15.
doi:10.1080/08827508.2019.1678156.
[5] X. Chen, X. Jin, H. Jiao, Y. Yang, J. Liu, Pore Connectivity and Dewatering Mechanism of
Tailings Bed in Raking Deep-Cone Thickener Process, Minerals. 10 (2020) 375.
doi:10.3390/min10040375.
[6] G. Liang, Q. Zhao, B. Liu, Z. Du, X. Xia, Treatment and reuse of process water with high
suspended solids in low-grade iron ore dressing, Journal Of Cleaner Production. 278 (2021)
123493. doi:10.1016/j.jclepro.2020.123493.
[7] C. Wang, J. Ding, R. Cheng, C. Liu, T. Chai, Data-Driven Surrogate-Assisted Multi-Objective
Optimization of Complex Beneficiation Operational Process, IFAC-Papersonline. 50 (2017)
14982-14987. doi:10.1016/j.ifacol.2017.08.2561.
[8] R. Dwari, S. Angadi, S. Tripathy, Studies on flocculation characteristics of chromite’s ore
process tailing: Effect of flocculants ionicity and molecular mass, Colloids And Surfaces A:
Physicochemical And Engineering Aspects. 537 (2018) 467-477.
doi:10.1016/j.colsurfa.2017.10.069.
[9] A. Leite, É. Reis, Cationic starches as flocculants of iron ore tailing slime, Minerals Engineering.
148 (2020) 106195. doi:10.1016/j.mineng.2020.106195.
[10] L. Zhu, W. Lyu, P. Yang, Z. Wang, Effect of ultrasound on the flocculation-sedimentation and
thickening of unclassified tailings, Ultrasonics Sonochemistry. 66 (2020) 104984.
doi:10.1016/j.ultsonch.2020.104984.
[11] Y. Zhao, L. Meng, X. Shen, Study on ultrasonic-electrochemical treatment for difficult-to-settle
slime water, Ultrasonics Sonochemistry. 64 (2020) 104978.
doi:10.1016/j.ultsonch.2020.104978.3.
[12] R. Jia, B. Zhang, D. He, Z. Mao, F. Chu, Data-driven-based self-healing control of abnormal
feeding conditions in thickening–dewatering process, Minerals Engineering. 146 (2020) 106141.
doi:10.1016/j.mineng.2019.106141.
[13] Y. Mikhlin, S. Vorobyev, A. Romanchenko, S. Karasev, A. Karacharov, S. Zharkov, Ultrafine
particles derived from mineral processing: A case study of the Pb–Zn sulfide ore with emphasis
on lead-bearing colloids, Chemosphere. 147 (2016) 60-66.
doi:10.1016/j.chemosphere.2015.12.096.
[14] T. Leistner, U. Peuker, M. Rudolph, How gangue particle size can affect the recovery of ultrafine
and fine particles during froth flotation, Minerals Engineering. 109 (2017) 1-9.
doi:10.1016/j.mineng.2017.02.005.
[15] J. Carpenter, S. Iveson, K. Galvin, Ultrafine desliming using a REFLUX™ classifier subjected to
centrifugal G forces, Minerals Engineering. 134 (2019) 372-380.
doi:10.1016/j.mineng.2019.02.013.
[16] E. Matiolo, H. Couto, N. Lima, K. Silva, A. de Freitas, Improving recovery of iron using column
flotation of iron ore slimes, Minerals Engineering. 158 (2020) 106608.
doi:10.1016/j.mineng.2020.106608.
[17] V. Morkun, S. Semerikov, S.Hryshchenko, K.Slovak, Environmental geo-information
technologies as a tool of pre-service mining engineer's training for sustainable development of
mining industry, CEUR Workshop Proceedings. 1844 (2017) 303-310.
[18] V. Morkun, N. Morkun, V.Tron, Distributed control of ore beneficiation interrelated processes
under parametric uncertainty. Metallurgical and Mining Industry. 7(8) (2015) 18-21.
[19] S. Rath, N. Dhawan, D. Rao, B. Das, B. Mishra, Beneficiation studies of a difficult to treat iron
ore using conventional and microwave roasting, Powder Technology. 301 (2016) 1016-1024.
doi:10.1016/j.powtec.2016.07.044.
[20] V. Morkun, N. Morkun, Estimation of the crushed ore particles density in the pulp flow based on
the dynamic effects of high-energy ultrasound, Archives of Acoustics. 43(1) (2018) 61-67.
[21] V. Morkun, N. Morkun, A. Pikilnyak, The adaptive control for intensity of ultrasonic influence
on iron ore pulp, Metallurgical and Mining Industry. 6(6) (2014) 8-11.
[22] S. Mahiuddin, S. Bondyopadhway, J. Baruah, A study on the beneficiation of indian iron-ore
fines and slime using chemical additives, International Journal Of Mineral Processing. 26 (1989)
285-296. doi:10.1016/0301-7516(89)90034-3.
[23] High intensity focused ultrasound simulator, Mathworks.com. (2021).
https://www.mathworks.com/matlabcentral/fileexchange/30886-high-intensity-focused-
ultrasound-simulator?s_tid=srchtitle (accessed 5 February 2020).
[24] V. Morkun, N. Morkun, V. Tron, Model synthesis of nonlinear nonstationary dynamical systems
in concentrating production using Volterra kernel transformation, Metallurgical and Mining
Industry. 7(10) (2015) 6-9.
[25] M. Mamina, R. Maganga, K. Dzwiti, An analysis of Zimbabwe's comparative advantage in the
beneficiation and value addition of minerals, Resources Policy. 69 (2020) 101823.
doi:10.1016/j.resourpol.2020.101823.
[26] Y. Chen, V. Truong, X. Bu, G. Xie, A review of effects and applications of ultrasound in mineral
flotation, Ultrasonics Sonochemistry. 60 (2020) 104739. doi:10.1016/j.ultsonch.2019.104739.
[27] V. Golik, V. Komashchenko, V. Morkun, V. Zaalishvili, Enhancement of lost ore production
efficiency by usage of canopies, Metallurgical and Mining Industry 7(4) (2015) 325-329.
[28] O. P. Kreuzer, M. Yousefi, V. Nykänen, Introduction to the special issue on spatial modelling
and analysis of ore-forming processes in mineral exploration targeting, Ore Geology Reviews.
119 (2020) 103391. doi:10.1016/j.oregeorev.2020.103391.
[29] New ZET 230 ADC module, technical characteristics, news, ZETLAB. (2021).
https://zetlab.com/en/new-zet-230-adc-module/ (accessed 15 February 2021).
[30] C. Besta, A. Kastala, P. Ginuga, R. Vadeghar, MATLAB Interfacing: Real-time Implementation
of a Fuzzy Logic Controller, IFAC Proceedings Volumes. 46 (2013) 349-354.
doi:10.3182/20131218-3-in-2045.00189.