Deep learning-based ash content prediction of coal flotation
For coal flotation, simple CNN can classify the various flotation conditions (air flow rate, frother dosage, slurry solids, froth depth, and collector dosage), and the classification accuracy is higher than that of the artificial neural network [27], [28]. Their success on CNN, as a flotation condition that can change the ash content, proves ...
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Flotation Machine
Machines with large specific surface areas are generally preferred for coal flotation, due to the fast flotation kinetics of coal and the large froth solids loadings. Flotation machines …
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Flow Field Characteristics and Flotation Efficacy in a …
Abstract. The design and optimization of flotation machines hold significant importance in enhancing the industrial-grade coal beneficiation process. In this research, …
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A comprehensive review on aeration methods used in flotation machines …
Bubble sizes that are discussed in the flotation area of current literature are usually in four size groups. The typical bubble size in conventional flotation machines is found to be in the range close to 1 mm, such as the data reported by several researchers which were 600–2500 μm (Rodrigues et al., 2007), 800–1600 μm (Shao, 2004), and …
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The application of machine learning models based on …
In this study, four different machine learning (ML) models were used to simulate the migration behavior of minerals during coal slime flotation based on particle characteristics (shape, size ...
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Prediction of Clean Coal Ash Content in Coal Flotation …
This study successfully achieved high-precision detection of the clean coal ash content in the coal froth flotation domain by integrating deep learning with the likelihood function. Methodologically, a novel data processing and prediction framework was established by combining a deep learning Keras neural network with the likelihood …
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Switching and optimizing control for coal flotation process …
Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and …
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Machine vision based monitoring and analysis of a coal column flotation
2020. TLDR. Computer vision and machine learning techniques are integrated for recognition of process conditions of a coal column flotation circuit using different intelligent algorithms and a predictive model is built. Expand. 10.
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Influence of impeller speed and cell volume on coal flotation
Self-aerating laboratory flotation machines are commonly used for batch tests. There are mainly two types of design parameters that influence the self-aerated flotation machine performance. The first design parameter is the impeller geometry, which includes size, shape, and number of rotor and stator blades [13], [14]. The design of the …
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Design, Modeling, Optimization and Control of Flotation …
Design, Modeling, Optimization and Control of Flotation Process. A special issue of Minerals (ISSN 2075-163X). This special issue belongs to the section "Mineral Processing and Extractive Metallurgy". Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 18167.
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Coal Flotation | SpringerLink
Coal flotation is characterized by the chemical and petro-graphical composition of coal and its rank. In addition, size and sp . gr. of coal particles, pulp density, rate and …
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Froth image clustering with feature semi-supervision …
Coal flotation mainly uses the difference between the surface hydrophilicity and hydrophobicity of coal particles caused by reagents, and takes advantage of air and coal slurry to form froth to carry clean coal in various flotation equipment [1, 2]. The flotation effect, that is, the quality of the clean coal product, is directly related to the ...
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Deep correlation and precise prediction between static …
1. Introduction. In the realm of froth flotation, one of the paramount criteria for evaluating flotation efficacy is the ash content present in the concentrate [1], [2].The ash content is universally acknowledged as a pivotal metric for the assessment of coal quality, a parameter of critical significance in various key sectors, encompassing power generation …
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Kinetic modelling of flotation column and …
coals below 500 µm. In the study, the flotation column and Jameson cell performances for three different. particle sizes (-500+300, - 300+212 and - 212+106 μm) were compared. For the first time ...
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Switching and optimizing control for coal flotation …
Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth …
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Machine vision based monitoring and analysis of a coal column flotation
A machine vision system was developed for monitoring a coal flotation column. •. An industrial coal flotation column was operated at different operating conditions. •. Algorithms for extracting visual and textural froth features were developed. •. Relationship between image variables and process variables was discussed.
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Gas Dispersion Characteristics in a Novel Jet-Stirring …
Flotation is a widely used and effective method for treating fine coal slime,1,2 and the flotation machine is the main equipment for completing this process.3 During the flotation process, useful mineral particles are adsorbed onto the surface of bubbles and transferred to a layer to become a
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The Life Cycle of Water Used in Flotation: a Review
In order to enhance the coal flotation in a high pulp density slurry, new equipment such as a flash flotation machine, hydraulic machine, and series flotation column were developed and applied in high pulp density flotation; e.g., Xie et al. combined a jet flotation column (JFC) and a cyclonic micro-bubble flotation column (FCMC) into …
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Flotation Process
The behavior of coal in the flotation process is determined not only by a coal's natural floatability (hydrophobicity), but also by the acquired floatability resulting from the use of flotation reagents. The general classification of the reagents for coal flotation is shown in Table 6.1 (Laskowski, 2001).
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An evaluation of machine learning and artificial
A total of 51 flotation tests were conducted on coal samples with 38% ash-content and a P 80 of approximately 49 μm. Different influencing variables of coal flotation including polymer dosage, pH, polymer conditioning time, sodium metasilicate dosage (commercial dispersant), and the impeller speed were used as inputs for the models.
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Recognition of process conditions of a coal column …
A machine vision is able to extract the froth features and present them to the plant operators or the process control system. In this communication, computer vision and …
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The application of machine learning models based on …
DOI: 10.1016/j.apt.2021.11.015 Corpus ID: 244782832; The application of machine learning models based on particles characteristics during coal slime flotation @article{Zhao2021TheAO, title={The application of machine learning models based on particles characteristics during coal slime flotation}, author={Binglong Zhao and …
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Flotation froth recognition system based on machine vision
Coal flotation mainly uses the difference between the surface hydrophilicity and hydrophobicity of coal particles, caused by their interaction with reagents, which results in the separation of clean and tail coal from coal slime in the flotation machine or flotation column [1, 2]. In the flotation process, the reagent dosage is the main factor ...
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Froth image feature engineering-based prediction method …
The image acquisition devices were installed above the second cell of flotation machine in a coal preparation plant in Zaozhuang, China. The 1/3 coking coal sample used for flotation was collected from Zaozhuang Mining area in China. The froth image acquisition set-up as realized in coal flotation circuit is shown in Fig. 1. Cover the …
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Effect of Hydrodynamic Cavitation Assistance on …
Firstly, a 60-g coal sample was placed in the flotation slot with 1 L tap water and agitated for 2 min. Then, the collector (kerosen e) was added into the slurry and mixed for 1 min.
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Influence of impeller speed and cell volume on coal flotation
It is a general practice to design the coal flotation circuit based on kinetics results derived from laboratory scale batch flotation. Usually, laboratory and plant flotation results are different; the collective evidence suggests that different machine sizes and designs can produce similar flotation performance when the operating variables ...
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Flotation froth image classification using convolutional neural
A machine vision system was installed on an industrial coal flotation column. •. A convolutional neural network (CNN) was developed to extract the froth features. •. A CNN-based classifier was applied to classify the froth images. •. Proposed classifier yielded much better performance than artificial neural networks.
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Influence of impeller speed and cell volume on coal flotation
To investigate the effect of slimes on the flotation recovery and kinetics of coal particles, batch flotation and flotation rate tests were carried out using flotation mixtures including slime ...
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Study on the effect of flow field optimization on flotation …
The findings demonstrate that altering the flow field pattern enhances the turbulence in the flotation machine's mixing zone, enhances the velocity distribution of the three-phase fluid at the bottom of the flotation tank, and fosters bubble-particle contact, collision, and adhesion. This can successfully reduce the clean coal ash content.
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Combined column and cell flotation process for …
particles that cannot be processed by the flotation machine to obtain the clean coal with qualified ash. content (Dey, Manjari, and Santosh 2013). Therefore, the flotation process using a ...
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