This study makes use of two knowledge discovery techniques for the identification of patterns of coal blending, and for the exploration of model results, with the aim of improving coke quality prediction models.
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Minimize variations in coal quality, ensure contract compliance, and improve efficiency with the Thermo Scientific CQM FLEX Coal Analyzer. The CQM FLEX is a full-featured coal quality analyzer that can incorporate either Prompt Gamma Neutron Activation (PGNAA) or Pulsed Fast Thermal Neutron Activation (PFTNA), and it provides the option of sourcing …
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Factors such as the pollutant formation, pollution emission punishment and pollutant control devices are considered to optimize the coal blending method for a 300 …
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Request PDF | A machine learning approach to improve ignition properties of high-ash Indian coals by solvent extraction and coal blending | Indian coals are of poor quality, having high ash ...
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The support vector machine (SVM) is used to establish the pollutant formation prediction model for the coal–fired boiler. Moreover, the model built above is trained and verified based on the actual operation data. Then the genetic algorithm is applied to optimize the coal blending method with the coal price to achieve the lowest operation …
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In this paper the coal blending optimization model consider the factors such as pollutant formation, pollution discharge punishment and pollutant control devices. Support vector …
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deviation state to avoid the occurrence of heavy equipment failure; the resistance coal level sensor is used to detect the coal level, and the coal level is started according to the coal level [6]. Stop the program to realize automatic coal blending. Finally, a …
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Coal blending optimization presents a complex and challenging task, as it encompasses multiple competing objectives, such as quality, cost, and environmental considerations.
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In this study, a multi-objective simulated annealing algorithm (MOSA)-based coal blending optimization approach in coking process is proposed. The objective function which …
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The order of system automatic start and stop, manual start and stop, automatic coal blending, fault interlock stop, and monitoring control requirements must comply with the principle: after the manual or automatic start signal is issued, the equipment in the PLC program control system extends in the direction of reverse coal flow Start in …
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This work provides the foundation of future studies in examining coal blending decisions, with the proposed parameter having the potential to be applied as part of a coke quality prediction model ...
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[6] Chen Huai Zhen, Chen Ya Fei et al 1999 Industrial analysis and calorific additivity of steam coal blending in China [J] Clean coal technology 5 51-54. Google Scholar [7] Wang Kai Ming and Cai Bin 2010 The role of coal quality analysis in coal blending testing [J] Coal processing and comprehensive utilization 28-29. Google Scholar
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In the coal blending and coking process, different types of coal are transported to a funnel by a stackerCreclaimer and blended in given proportions to form the corresponding blended coal, which is sent to the coal tower. ... The dataset used for the problem is established using machine vision techniques. An improved bald eagle …
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To improve coal quality and reduce coal blending costs, we need to predict the coke quality and optimize the coal blending scheme. In this paper, we propose a …
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This study aims to develop a machine learning (ML) model to optimize biomass-coal co-gasification. ... °C, while air and temperatures around 1570 °C yielded the best outcomes for the Fischer-Tropsch process. A biomass/coal blending ratio between 50 % and 70 % was found to be suitable for almost all gasifying agents under both criteria. …
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The coal blending optimization model consists of NOx prediction model and SO2 prediction model and aims to minimize the coal blending cost. The structur e of the coal blending optimization model is shown as Fig1. The NO x prediction model is based on SVM [4]; The SO 2 concentration in flue gas is calculated
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Major blending types include (i) coal-coal [10], (ii) coalbiomass [11] and (iii) coal-opportunity fuel [12] mixtures. The coalcoal blending is often used to reduce sulfur content, control the ...
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A Machine Learning Approach to Improve Ignition Properties of High-ash Indian Coals by Solvent Extraction and Coal Blending Srishti Mittal a,b, Shailesh Pathak a, Heena Dhawan a, Sreedevi Upadhyayula a * a Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India b Department of …
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The characteristics of HGI fractions of the blend coal were investigated. One rejected coal (A) with three imported coals, Indonesian coal (B), Russian coal (G) and Australian coal (H), and their blends were tested for their grindability indices as per standard ASTM D 409. The fractions obtained from HGI tests were further assessed for …
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Structure optimization of coal blending equipment in coking. Qiang Yin 1, Zhichao Xiong 1, Quanguo Zhang 1 and Jiabing Hu 2. Published under licence by IOP Publishing Ltd IOP Conference Series: Materials Science and Engineering, Volume 423, 4th International Conference on Applied Materials and Manufacturing Technology 25–27 …
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Co-firing coal and biomass has been applied in existing coal-fired power stations recently. Online blend-type identification was investigated by support vector machine (SVM) using flame emission ...
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Finally, Particle Swarm Optimization (PSO) is used to optimize coal blending and air distribution schemes, effectively reducing severe corrosion ratio from 36.34 % to 10.04 % in a typical case by improving the atmosphere near the water walls. ... In recent years, researchers have increasingly used machine learning to model and analyze data in ...
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The controlling objects are more, such as belt conveyor, coal breaker, sifting machine, ring type coal feeder, impeller coal feeder, belt feeder, vibration feeder, bucket wheel stacker ... Blending control function includes automatic coal blending, remote manual blending and local manual blending, coal blending system has perfect function of ...
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DOI: 10.1016/j.cej.2020.127385 Corpus ID: 225176220; A machine learning approach to improve ignition properties of high-ash Indian coals by solvent extraction and coal blending
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Multi-objective optimization of coal blending is a research hotspot of process optimization in coking industry, and its fundamental goal is to study how to effectively …
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Depending on the properties of the coal used, a prehomogenising or buffer store is used. Blending effect. The blending effect [ H=Sin/Sout ] of a homogenising stacker/reclaimer system is generally determined as the ratio between the standard deviation Sin of one leading chemical parameter of the store input and the standard deviation . Methods
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Coal blending is used to mix the coal with different types of coal or biomass with the main purpose of increasing Cl content, which favors the transformation of Hg0 to Hg2+ …
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In this section, we first show how to use the results of the quality prediction model to construct a multi-objective optimization algorithm for coal blending, and then proposes …
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As Fig. 1 illustrates, the method for rapidly obtaining chemical species distributions through a POD reduced-order model to evaluate high-temperature corrosion degrees and optimize coal blending and air distribution to reduce the risk of high-temperature corrosion of water walls includes four steps: CFD simulation under different operating conditions, chemical …
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Supposing the costs of three blending coals are C1, C2, C3.., we can the get the objective function as 332211 ***)( XCXCXCxMinF ++= (1) • Constraints: Sub-varieties of quality inspection -50mm Raw coal lump coal breaking Coal warehouseClean coal Coal warehouse Electrical vibration convey coal machine Electrical vibration …
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The correlations between blending-ash compositions and their AFT have been investigated by support-vector machines and linear least squares [21], [22]. ... Coal blending is a promising way to regulate the ash-fusion characteristics of coal to meet gasification requirements. Variations in ash-fusion behavior of three high-AFT coals and …
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machine convey coal machine Belt conveyer Belt conveyer Blending Coal warehouse Sale Optimizing the ratio Figure.1 Flow chart of coal blending process G. Xi-jin et al. / Procedia Earth and Planetary Science 1 (2009) 654–660 655
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DOI: 10.1016/j.ins.2020.02.072 Corpus ID: 213497699; Modeling and optimization of coal blending and coking costs using coal petrography @article{Yuan2020ModelingAO, title={Modeling and optimization of coal blending and coking costs using coal petrography}, author={Yan Yuan and Qilin Qu and Luefeng Chen and Min Wu}, …
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