In this study, the gross calorific value (GCV) of coal was accurately and rapidly determined using eight artificial intelligence models based on big data of 2583 observations of coal samples in the Mong Duong underground coal mine (Vietnam). Accordingly, the volatile matter, moisture, and ash were considered as the key variables (inputs) for determining GCV. Seven artificial neural network ...
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.
IoTenabled sensor devices and machine learning methods have played an essential role in monitoring and forecasting mine hazards. In this paper, a prediction model has been proposed for improving the safety and productivity of underground coal mines using a hybrid CNNLSTM model and IoTenabled sensors. The hybrid CNNLSTM model can extract ...
Accumulators give off a circuit network signal. You can wire them to a power switch to isolate your steam engines as long as demand is being met elsewhere. If the accumulator falls below a threshold, toggle the engines back on. Look up how to make an SR latch (aka a memory toggle) with combinators.
Professor Shan Pengfei adopted a coalrock identification method based on machine deep learning FasterRCNN, which realized the accurate identification and location of coal seam and rock stratum ...
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 ...
Coal power plant cycling 1. Introduction The use of renewable energy sources (RESs) globally is projected to reach up to 30% by the end of 2030 [1]. In 2020, RES accounted for 21% of all the electricity generated in the United States [2]. The RESs, such as wind and solar, are considered as intermittent generating sources due to climatic conditions.
Spontaneous combustion of coal leading to mine fire is a major problem in most of the coal mining countries in the world. It causes major loss to the Indian economy. The liability of coal to spontaneous combustion varies from place to place and mainly depends on the coal intrinsic properties and other geomining factors. Hence, the prediction of spontaneous combustion susceptibility of coal is ...
Coal mines operated without electricity. Electricity began to be adopted in mining and manufacturing in the late 1880s and the 1890s. (Electricity was first introduced into Ohio's bituminous coal mines in 1889.) The introduction of electricity in coal mines greatly facilitated the introduction of laborsaving machinery. 1891.
Get Price Quote. Voltage : 220V Capacity : 3000 Kgs to 3900 Kg per hour Weight : kg Power Consumption : 1 Hp to 30 Automatic Grade : Automatic used in chemicals, lime stone. bricks industries to make the coal briquettes for firing in furnaces and boilers. by this machine coal briquettes can be made in many shapes designs from coal dust powder with binding material. also used to ...
Identification of coal and gangue is one of the important problems in the coal industry. To improve the accuracy of coal gangue identification in the coal mining process, a coal gangue identification method based on histogram of oriented gradient (HOG) combined with local binary pattern (LBP) features and improved support vector machine (SVM) was proposed. First, according to the actual ...
Coal mine gas accident is one of the most serious threats in the process of safe coal mine mining, making it important to accurately predict coal mine gas emission. To improve the accuracy of coal mine gas emission prediction, a hybrid machine learning prediction model combining random forest (RF) algorithm, improved gray wolf optimizer (IGWO) algorithm and support vector regression (SVR ...
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 ...
Therefore, this manuscript proposes a new identification method of surface cracks from UAV images based on machine learning in coal mining areas. First, the acquired UAV image is cut into small subimages, and divided into four datasets according to the characteristics of background information: Bright Ground, Dark Dround, Withered Vegetation ...
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.
Accordingly, eigenvectors of coal and rock images are computed based on thermal imaging cloud images from coal and rock cutting trials. The traditional recognition technology of coal and rock mainly adjusts the height of the drum of the coal winning machine by manually observing the state of coal and rock and listening to the sound.
Coal has been one of the most important sources of primary energy, together with oil and natural gas, for many decades now. Approximately onethird of the world's energy and 40% of electricity is generated from coal, which will remain an important part of the global energy mix in the medium to long term [1,2].During the early extraction of coal resources, the roomandpillar mining method ...
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 ...
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 (, ).
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 ...
Coloradobased TriState Generation and Transmission Association is proposing an energy plan that will close two coal power plants and significantly boost the amount of renewable energy sources on its system.. TriState filed the new electric resource plan with state regulators Friday. The wholesale power supplier is seeking up to 970 million in grants and loans through the Department of ...
However, in the prediction of coal and gas outbursts, it is difficult or impossible to collect some index data when an accident occurs, which makes less data available for algorithm learning. Therefore, the prediction of coal and gas outbursts based on machine learning is still in the theoretical research stage.
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.
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 ...
Abstract. The calorific value of coal is important in both the direct use and conversion into other fuel forms of coals. Accurate calorific value predicting is essential in ensuring the economic, efficient, and safe operation of thermal power plants. Least squares support vector machine (LSSVM) is a variation of the classical SVM, which has ...
Chemical analysisbased, imagebased, and machinelearningbased methods are widely used for coal identification. The chemical analysisbased method is reliable and relatively accurate. However, this method requires stringent analysis techniques for elemental content, and it is easily affected by foreign chemical substances.
sieving machine sor ts raw coal into coal equal to or greate r than 100 mm and less than 100 mm; a transp ortation syste m is used to transport the coa l from underground to grou nd; and
India aims to add 17 gigawatts of coalbased power generation capacity in the next 16 months, its fastest pace in recent years, to avert outages due to a record rise in power demand, according to ...
The imageanalysis based sensors are the most appropriate detection method at present. One option to detect coal quality via multiinformation online is the machine vision detection based on CCD/CMOS industrial cameras, which provides advantages including safety, convenient installation, and highcost performance.
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 ...
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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