WEBApr 26, 2023 · The problem of dust pollution in the openpit coal mine significantly impacts the health of staff, the regular operation of mining work, and the surrounding environment. At the same time, the openpit road is the largest dust source. Therefore, it analyzes the influencing factors of road dust concentration in the openpit coal mine. It is of practical .
WEBJun 1, 2022 · 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.
WEBMay 1, 2023 · 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 .
WEBApr 1, 2017 · The thickness of tectonically deformed coal (TDC) has positive correlation associations with gas outbursts. In order to predict the TDC thickness of coal beds, we propose a new quantitative predicting method using an extreme learning machine (ELM) algorithm, a principal component analysis (PCA) algorithm, and seismic attributes.
WEBMay 1, 2013 · A neural network prediction method based on an improved SMOTE algorithm expanding a small sample dataset and optimizing a deep confidence network was proposed, which can be used to better predict and analyze coal mine water inrush accidents, improve the accuracy of water in rush accident prediction, and encourage the .
WEBOct 22, 2021 · Appliion of Volume Detection Based on Machine Vision in Coal and Gangue Separation. October 2021. DOI: / Conference: 2021 IEEE 5th Conference on Energy Internet and ...
WEBDOI: / Corpus ID: ; Experimental analysis of vibratory screener efficiency based on density variation for screening coal and iron ore article{Shanmugam2023ExperimentalAO, title={Experimental analysis of vibratory screener efficiency based on density variation for screening coal and iron ore}, .
WEBApr 12, 2022 · Machine learning prediction of calorific value of coal based on the hybrid analysis. April 2022. International Journal of Coal Preparation and Utilization 43 (1):122. DOI: / ...
WEBJan 30, 2014 · This paper presents a new online coal identifiion system based on support vector machine (SVM) to achieve online coal identifiion under variable combustion conditions.
WEBDec 8, 2023 · Liu et al. realized the approximate analysis of coal based on laserinduced breakdown spectra by combining principal component regression, artificial neural network, and PCAANN models. All of the above methods are used to deal with highdimensional spectral data using machine learning, but the direct use of machine learning algorithms .
WEBJun 1, 2019 · Wang et al. [13] constructed a classifiion model of coal based on a confidence machine, a support vector machine algorithm and nearinfrared spectroscopy, and a good classifiion result was obtained.
WEBFeb 1, 2024 · Coal structure identifiion based on PSOSVM. In this study, the coal structure prediction model was established based on 175 sets of data (53 undeformed coal, 67 aclastic coal and 54 granulated coal) from 20 wells, excluding 10 sets of data from the No. 3 coal seam in Well M19 (4 undeformed coal, 1 aclastic coal and 2 .
WEBOct 22, 2023 · The belt conveyor is a key piece of equipment for thermal power plants. Belt mistracking causes higher economic costs, lower production efficiency, and more safety accidents. The existing belt correction devices suffer from poor performance and high costs. Therefore, a design method for coal conveying belt correction devices is proposed in .
WEBApr 1, 2023 · In this study, we used machine learning based approach to classify fuels with the use of proximate analysis results,, fixed carbon, volatile matter and ash contents.
WEBJul 1, 2022 · Abstract. In this paper, YOLOv4 algorithm based on deep learning is used to detect coal gangue. Firstly, the data set of coal gangue was made, which provides sufficient data for the training and verifiion of the detection algorithm model. Then, the coal gangue data set was used to test the influence of the combined use of optimization ...
WEBKeeping in mind the various problems related to gas leakage causing accidents in the coal mine, this paper depicts coal monitoring system using wireless sensor networks and IoT, which can monitor the various gas and temperature parameters and take action with the help of multimodal logistic regression algorithm applied on the real time collected data .
WEBSpontaneous 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 oth .
WEBSep 1, 2021 · Among them, the sensorbased equipment is a hightech classifiion method with high efficiency, low cost, and no pollution, so it has the potential for mineral preenrichment and presorting in industrial appliions. At present, sensorbased ore sorting technology is mainly divided into two types: ray sensorbased and machine .
WEBJul 26, 2018 · OAPA. Coal exploration based on the MELM model and Landsat 8 satellite images: (a) image taken on July 5th, 2015; (b) image taken on May 4th, 2016; (c) image taken on June 24th, 2017; (d) Google ...
WEBSep 1, 2023 · Based on reverse engineering, this paper discusses the process of localization and development of imported coal machine reducers and focuses on the five steps from the reducer design stage.
WEBDec 13, 2023 · The HTG diagrams are established based on previous work by Liu et al. 72 using coal as the investigated feedstock. HHV higher heating value, ER energy recovery, CR carbon recovery.
WEBSep 1, 2021 · The workflow combines physicsbased simulation, laboratory experiments, and a datadriven machine learning approach for estimating the permeability profile. As part of this workflow, several coal specimens from the study coal seam are first tested under different stresses to measure their permeability, density, and ultrasonic responses.
WEBMar 23, 2022 · The technology of microseismic monitoring, the first step of which is event recognition, provides an effective method for giving early warning of dynamic disasters in coal mines, especially mining water hazards, while signals with a low signaltonoise ratio (SNR) usually cannot be recognized effectively by systematic methods. This paper .
WEBMar 15, 2024 · The life cycle inventory of coal power generation in China was obtained from the CPLCID® (Chinese processbased life cycle inventory database, Zhang et al., 2016), which primarily includes an internationally peerreviewed inventory of subcritical, supercritical, and ultrasupercritical technologies for coal power generation (Hong et al., .
WEBBituminous coal is the most abundant rank of coal found in the United States, and it accounted for about 46% of total coal production in 2022. Bituminous coal is used to generate electricity and is an important fuel and raw material for making coking coal for the iron and steel industry. Bituminous coal was produced in at least 16 states ...
WEBNov 20, 2022 · Based on differences in coal rock texture features, Meng and Li put forward a GLCM and BPNNbased coal rock interface identifiion 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 .
WEBJun 3, 2021 · This paper uses this as a starting point to propose a distributed support vector machine model based on a cloud computing platform. The model is based on the existing popular MapReduce distributed computing framework, and completes the classifiion and prediction work in the coal system in a distributed manner. ... Environmental cost control ...
WEBJul 26, 2018 · Third, we proposed a multilayer extreme learning machine algorithm and constructed a coal classifiion model based on that algorithm and the spectral data. The model can assist in the classifiion of bituminous coal, lignite, and noncoal objects.
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