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 ...
Research on Multistep Mixed Predictiom Model of Coal Gasifier Furnace Temperature Based on Machine Learning February 2022 Journal of Physics Conference Series 2187(1):012070
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 ...
According to Table 1, the response time of belt conveyor deviation correction system based on machine vision is less than s, and the maximum difference between the deviation detected by machine vision and the actual deviation of sensor is only cm. Thus, this system is capable of quick and effective detecting conveyor belt deviation.
A novel approach based on binocular machine vision and genetic algorithmbackpropagation neural network (GABPNN) was proposed. First, the sample image was segmented, and each region was judged to be coal or gangue. ... Prediction of density and sulfur content level of highsulfur coal based on image processing. Powder Technol., 407 (2022), p ...
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
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 ...
Clustering, Classification, and Quantification of Coal Based on Machine Learning Clustering Models. Clustering is a type of unsupervised learning method, which extracts the data features only based on the LIBS spectra instead of category labels, including principal component analysis (PCA), Kmeans clustering, DBSCAN clustering, etc. The ...
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 ...
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 ...
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.
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.
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 ...
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 ...
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 ...
Abstract. The higher heating value (HHV) of 84 coal samples including hard coals, lignites, and anthracites from Russia, Colombia, South Africa, Turkey, and Ukrania was predicted by multilinear regression (MLR) method based on proximate and ultimate analysis data. The prediction accuracy of the correlation equations was tested by Analysis of variance method. The significance of the predictive ...
Based on the system theory of man, machine, environment, and management, and taking the four single elements and the whole system in a coal mine as the research object, this paper systematically analyzes and studies the evaluation and continuous improvement of coal mine intrinsic safety.
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 ...
et al. [29] used a machine learning model to develop an acceptable coal ash model based on a variable block width incremental random configuration network and proposed an online adaptive semisupervised learning based proper coal ash model [30]. Machine learning tools have been shown to have the ability to provide datadriven mechanical ...
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 ...
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 (, ).
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.
Based on differences in coal rock texture features, Meng and Li put forward a GLCM and BPNNbased coal rock interface identification method. Wu and Tian ; Wu, Zhang proposed a ... Deep learning is a machine learning method based on a deep network model. To be specific, inspired by the concept of "receptive field" in the biological community ...
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 ...
Coal is the most abundant fossil fuel on Earth. Its predominant use has always been for producing heat energy. It was the basic energy source that fueled the Industrial Revolution of the 18th and 19th centuries, and the industrial growth of that era in turn supported the largescale exploitation of coal deposits. Since the mid20th century, coal has yielded its place to petroleum and natural ...
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