Therefore, based on the analysis of humanmachine interaction in intelligent coal mine hoisting machine room, considering the applicability of SRK model and the understanding of IDA model on the ...
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Coal burst has become a worldwide problem that needs to be solved urgently for the sake of coal mine safety production due to its complicated triggering mechanisms and numerous influencing factors. The risk assessment of coal burst disasters is particularly critical. In this work, 15 factors affecting coal burst occurrence are selected from the perspectives of geodynamic environment and ...
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The four elements (man, machine, environment, and management) in the coal mine and their synthesis are calculated and analyzed by using the Matlab tool and the BP neural network program. The predicted value of the personnel intrinsic safety value is (). The intrinsic safety value of the equipment is (, ).
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The underground coal mines (UCM) exhibit many lifethreatening hazards for mining workers. In contrast, gas hazards are among the most critical challenges to handle. This study presents a comparative study of the sensor fusion methodologies related to UCM gas hazard prediction and classification. The study provides a brief theoretical background of the existing methodologies and their usage to ...
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At present, coal gangue sorting technology based on machine learning is widely used . Liu C et al. established a comprehensive identification model of different ores and a support vector machine model through the texture characteristics of an image and completed the identification of different ores, thereby improving the efficiency of coal and ...
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The main obstacle for machine and equipment use that allow coil processing is the quantity to be processed. Naturally, when only a few parts need to be made, sheet metal is the best solution. But even in the case of mediumsized batches, the coil technology is still not very successful, as coil replacement and "production changeover" times ...
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Coal has been used as the most commonly energy source for power plants since it is relatively cheap and readily available. Thanks to these benefits, many countries operate coalfired power plants. However, the combustion of coal in the coalfired power plant emits pollutants such as sulfur oxides (SOx) and nitrogen oxides (NOx) which are suspected to cause damage to the environment and also be ...
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Subsequently, a multiscale linear filter based on the Hessian matrix and Gaussian function was developed to obtain the edge intensity image. Finally, Experiment. The detection experiment of the coal content in gangue was carried out on the test rig shown in Fig. 10. The experimental samples were collected from the Hongliu coal preparation plant.
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There exist many works where machine learning has been used for both simulated and physical optimization of combustion systems. Zheng et al. combine a support vector machine (SVM) with ant colony optimization (ACO) to optimize a 300 MW plant based on predicted NO x values (Zheng et al., 2008). Zheng et al. also compare the performance of ACO to ...
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1. Introduction. Metal, as a limited natural resource, is an essential material for global economic development (Sykes et al., 2016).For example, Al and Fe have been widely used in building construction and machinery manufacturing (Soo et al., 2019), V is an important metallic material used in the production of ferrous and nonferrous alloys (Gao et al., 2020), and Cr has been used in ...
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The aim of this study was to predict the high risk of nodular thyroid disease in coal miners based on five different Machine learning (ML) is a retrospective clinical study in which 1,708 coal miners who were examined at the Huaihe Energy Occupational Disease Control Hospital in Anhui Province in April 2021 were selected and ...
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Monitoring and enforcing the performance of equipment in coalbased thermal power plants play a vital role in operational management. As the coalbased power plant is a nonlinear system involving multiple inputs and multiple outputs, the standard and typical identification methods tend to deviate. This can happen due to factors such as strong coupling, multivariable characteristics, time ...
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In previous research, many scientists and researchers have carried out related studies about the spontaneous combustion of coal at both the micro and the macro scales. However, the macroscale study of coal clusters and piles cannot reveal the nature of oxidation and combustion, and the mesoscale study of coal molecule and functional groups cannot be directly applied to engineering practice ...
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In our previous work, an approach based on image analysis and particle swarm optimizationsupport vector machine was presented (Wang et al. 2021) to detect the coalcarrying rate in gangue ...
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Longwall Miner. Twenty percent to 30 percent of mined coal underground is from longwall mining. This is performed by a mechanical cutter that shears coal off from a panel on the seam. The panel being worked on may be up to 800 feet in width and 7,000 feet in length. Mined coal is deposited onto a conveyor that moves the coal to a collection area.
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Product quality monitoring is one of the most critical demands in the coal industry. Conventional coal quality analysis is offline, laborious, and lagging behind coal production. Using machine vision for determining ash content in coal has been recently developed. However, there are some challenges in the model design due to its task complexity.
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Coal resources play a crucial role as an energy source in China and have contributed immensely to the country's economic development [1,2], and given China's current energy structure, coal is expected to maintain its dominant position in the energy supply for the foreseeable future [].Based on statistics from the National Bureau of Statistics, China is endowed with abundant coal resources ...
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This report presents the results of an exploratory machine learningbased analysis of green stormwater infrastructure asset data across five cities in the United States. Within each city, authors evaluated the location of installed green stormwater infrastructure based on the demographic and land use characteristics of the surrounding area.
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Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model As the core of artificial intelligence, machine learning has strong application advantages in multicriteria intelligent evaluation and decisionmaking. The level of sustainable development is of great significance to the safety evaluation of coal mining enterprises.
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Here, a modeling method based on feature fusion and long shortterm memory (LSTM) network is proposed to mine the spatial and temporal coupling relationship between input variables for improving the prediction accuracy. ... Prediction of SOxNOx emission from a coalfired CFB power plant with machine learning: Plant data learned by deep neural ...
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The CIM is a joint product of the Massachusetts Institute of Technology and the Rhodium Group that catalogs and maps clean energy investments before and after the IRA passed. This work reflects an update and extension to our initial placebased analysis in The Inflation Reduction Act and Business Investment (August 2023). We offer two ...
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The machine learning models were optimized using hyperparameter tuning, and the most successful model was selected based on its regression and computational cost performance. Sensitivity analysis was conducted to investigate the performance of the coal properties on total desorbed gas content.
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Large foreign object transporting by coal mine conveyor belt may lead to production safety hazards. To reduce safety accidents during coal mining, a large foreign object detection method based on machine vision is proposed in this paper. An adaptive weighted multiscale Retinex (MSR) image enhancement algorithm is proposed to improve the captured image quality of the belt conveyor line. An ...
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article{osti_, title = {Development of novel dynamic machine learningbased optimization of a coalfired power plant}, author = {Blackburn, Landen D. and Tuttle, Jacob F. and Andersson, Klas and Fry, Andrew and Powell, Kody M.}, abstractNote = {The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coalfired boilers now routinely ramp up and down.
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Coal is a black or brownishblack sedimentary rock that can be burned for fuel and used to generate is composed mostly of carbon and hydrocarbons, which contain energy that can be released through combustion (burning). Coal is the largest source of energy for generating electricity in the world, and the most abundant fossil fuel in the United States.
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Coal Classification Method Based on Improved Local Receptive FieldBased Extreme Learning Machine Algorithm and VisibleInfrared Spectroscopy PMC Journal List ACS Omega (40); 2020 Oct 13 PMC As a library, NLM provides access to scientific literature.
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A material supplier from Belgium would like to produce limestone powder for his custome...
India is rich in various mineral resources and it is an important mineral processing market
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