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:Thickener ControlL. Bergh, P. Ojeda, L. TorresPublish Year:2015
Identification and Control of an Industrial Thickener Using
Identification and Control of an Industrial Thickener Using Historical Data Abstract: In the mining industry, thickeners are used to increase density of slurries by removing water.
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:Thickener ControlSlurry ThickenerFunction of ThickenerStructure of Thickener · Auditing the operation of a thickener requires knowledge of the thickening parameters, the efficiency of flocculation, the dilution in the feedwell, the sediment and
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International Journal of Mining Science and Technology
Fig. 1. Computing mesh for the industrial thickener. 886 M. Ebrahimzadeh Gheshlaghi et al./International Journal of Mining Science and Technology 23 (2013) 885–892 data.AscanbeseeninFigs.2and3
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· Consider the design of an industrial thickener for a feed rate of 178 tph, with an underflow concentration of 57.3% of solid by weight of a copper tailing with the following properties: Solid density ρ s = 2500 kg/m 3 Liquid density ρ f = 1000 kg/m
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Intelligent control of an industrial thickener-Semantic Scholar
DOI: 10.1109/ICARCV.2014.7064356 Corpus ID: 15159036 Intelligent control of an industrial thickener @article{Ojeda2014IntelligentCO, title={Intelligent control of an industrial thickener}, author={Pablo Ojeda and Luis G. Bergh and Luis Torres}, journal={2014 13th
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· the classical BDAC formulation and presents a real implementation of the enhanced BDAC technique to a real industrial paste thickener. Discover the world's research 25+ million members 160
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· Conventional feedback control has not been effective in stabilizing the process operation when the characteristics of the feed changes over time, since process dynamics exhibits high non-linearity. This work presents an expert system for an industrial thickener. Main results are a reduction in flocculants consumption and a more stable
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· This work presents an intelligent control based on an expert system applied to an industrial 125 m diameter thickener, processing 13000 m3/h of concentrate containing a 27 % of solids.
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An intelligent control strategy for thickening process
2020. TLDR. This article presents a real implementation of a neural network-based model predictive control scheme (NNMPC) to control an industrial paste thickener over an Industrial Internet of Things platform designed using the seven layer reference model for IIoT systems. Expand.
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· 1. Definition and Purpose. Mining thickeners, also known as clarifiers or settlers, are large sedimentation tanks used in mineral processing operations. They are designed to separate solids from liquids, allowing for the efficient concentration of solids and the recovery of valuable minerals.
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working of an industrial thickener
2022-09-18T00:09:17+00:00 working of an industrial thickener working of an industrial thickener For each project scheme design, we will use professional knowledge to help you, carefully listen to your demands, respect your opinions, and use our professional teams
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Expert Control Tuning of an Industrial Thickener-Academia.edu
The thickener is 150 m diameter and was designed to process 13000 m3/h of pulp, containing 27% of solids, with a specific gravity of 1.2, to deliver an underflow with a 54% of solids. The flocculants is added at a rate of 15g/ton of pulp or about 270 m3/h of a solution with a low flocculants concentration (0.02%).
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· In this paper, a constrained MPC is developed to control an industrial thickener. The control approach considers underflow slurry density as the controlled variable, along with four state variables (overflow turbidity, bed level, rake torque, and cone pressure) representing process constraints.
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· Computing mesh for the industrial thickener. Flow rate of the launder and bottom of the thickener verses the feed flow rate, 22.5% as solid percent. Height of settled bed verses the feed
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ALTERNATIVES TO NATROSOL AS THICKENER IN THE
Paints can be classified based on composition, end-use, method of cure and appearance (Morgan, 1990). The types of paints commonly used are: latex or emulsion paints, oil-based or gloss paints
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Application of Robust Model Predictive Control Using Principal Component Analysis to an Industrial Thickener…
Application of Robust Model Predictive Control Using Principal Component Analysis to an Industrial IEEE Transactions on Control Systems Technology ( IF 4.8) Pub Date : 2024-01-26, DOI: 10. Runda Jia, Fengqi You
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Application of Robust Model Predictive Control Using Principal Component Analysis to an Industrial Thickener
A data-driven robust model predictive control (DRMPC) method is used in this brief to control an industrial thickener. To estimate the future states of the thickener, a discrete-time linear time-invariant (LTI) model is employed using the data information from the pressure sensors installed inside the thickener. The hard constraints on the amount of dry ores in
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Settling characteristics of ultrafine iron ore slimes
3.2. Simulation of industrial thickeners The simulation study on an industrial thickener was car-ried out based on the settling of particles. The continuous thickener design procedure gives the inputs of thickener feed rate, which provides the required area to
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:Publish Year:2017Thickener
Intelligent control of an industrial thickener-Semantic Scholar
This work presents an intelligent control based on an expert system applied to an industrial 125 m diameter thickener, processing 13000 m3/h of concentrate containing a 27 % of
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· Guar gum printing thickener is an important component in textile industry because of a number of uses. Guar gum for textile printing aids in direct painting on wool, nylon and silk. They are also use in printing dyes on cotton fabric, carpet printing, acrylic blanket printing, burn out printing and vat discharge.
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· A rake torque model is validated with industrial plant data. By utilising the monotonic property of the rake torque model, a linear model predictive control (MPC) approach is developed to deal
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· Thickener developments have been driven by industry and academic in itiatives from the last 20-30 years (e.g. CFD modelling, AMIRA R esearch) but feedback from thes e implementation steps have
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· Abstract and Figures. Aqueous slurries’ dewatering using gravity-driven thickeners is an essential unit operation in mineral processing. Thickener feed dilution is often used for enhanced
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· Abstract. The Big Data revolution refers to using a large amount of data to improve decision making. In process control applications, the use of big data techniques has been restricted to complementing classical control schemes as model-based or PID approaches. This work focuses on a model-free purely data-driven control strategy
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Beginners guide to thickeners-Metso
Beginners guide to thickeners. Thickening is a process where a slurry or solid-liquid mixture is separated to a dense slurry containing most of the solids and an overflow of essentially clear water (or liquor in leaching processes). The driving force for the separation is gravitational, where the differences in phase densities drive the
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Beginners guide to thickeners-Metso
Thickening is a process where a slurry or solid-liquid mixture is separated to a dense slurry containing most of the solids and an overflow of essentially clear water (or liquor in
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Expert Control Tuning of an Industrial Thickener
On the control of sludge level and underflow concentration in industrial thickeners. J. P. Segovia F. Concha D. Sbarbaro. Engineering, Environmental Science. 2011. Abstract The rational use of water in the mineral processing industry has become an important issue due to the geographical location of many plants.
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:Thickener ControlSlurry ThickenerPublish Year:2021 · This work presents an intelligent control based on an expert system applied to an industrial 125 m diameter thickener, processing 13000 m 3 /h of
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· This article presents a real implementation of a neural network-based model predictive control scheme (NNMPC) to control an industrial paste thickener over an Industrial Internet of Things platform designed using the seven layer reference model for IIoT systems. This article presents a real implementation of a neural network-based
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· This work presents an intelligent control based on an expert system applied to an industrial 125 m diameter thickener, processing 13000 m 3 /h of concentrate containing a 27 % of solids. Main results are a reduction in flocculants consumption and a more stable operation, with few emergency conditions.
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