MTW European Type Trapezium Mill
Input size:30-50mm
Capacity: 3-50t/h
LM Vertical Roller Mill
Input size:38-65mm
Capacity: 13-70t/h
Raymond Mill
Input size:20-30mm
Capacity: 0.8-9.5t/h
Sand powder vertical mill
Input size:30-55mm
Capacity: 30-900t/h
LUM series superfine vertical roller grinding mill
Input size:10-20mm
Capacity: 5-18t/h
MW Micro Powder Mill
Input size:≤20mm
Capacity: 0.5-12t/h
LM Vertical Slag Mill
Input size:38-65mm
Capacity: 7-100t/h
LM Vertical Coal Mill
Input size:≤50mm
Capacity: 5-100t/h
TGM Trapezium Mill
Input size:25-40mm
Capacity: 3-36t/h
MB5X Pendulum Roller Grinding Mill
Input size:25-55mm
Capacity: 4-100t/h
Straight-Through Centrifugal Mill
Input size:30-40mm
Capacity: 15-45t/h
Xiao Weili coal deep processing
Coal Identification Based on Reflection Spectroscopy and Deep
2022年7月7日 Deep learning (DL) has been extensively applied in various fields 16 − 18 DL is capable of building endtoend analytical models without relying on preprocessing 19, 20 Xiao 2022年6月29日 Xiao et al extracted spectral data features through a deep belief network and then constructed the coal analysis model using a derivative function with a regularization two Coal Identification Based on Reflection Spectroscopy and Deep In consideration of the importance of multiscale characterization of coal fractures for understanding the mechanisms of multiscale fluid transportation, we propose a new approach Weili GONG Professor (Full) Ph D State key laboratory for 2021年12月16日 We propose a novel method for coal granularity estimation based on a deep neural network called ResSSD to deal with the problem Then, to further improve the Full article: Robust coal granularity estimation via deep neural
Rapid proximate analysis of coal based on reflectance
2023年2月15日 In this paper, we propose a rapid analysis method for coal combining deep learning and spectroscopy, which utilizes a CNN network composed of dilated convolution and 2020年9月1日 They selected the most useful wavelengths for determining the properties of coal by the nearinfrared spectroscopy of coal, and established a coal quality prediction model by Rapid analysis of coal characteristics based on deep learning and approach combining deep learning with reflection spectroscopy for rapid coal identification in mining, combustion, and pyrolysis scenarios First, spectral data of different coal samples Coal Identification Based on Reflection Spectroscopy and Deep In this study, we proposed a multimodal deep learning technique, namely ClipIRMol (contrastive languageimage pretraining for infraredmolecule), for predicting coal molecular fragments Construction of macromolecular model of coal based on deep
Rapid analysis of coal characteristics based on deep learning and
提出了一种带正则化的二层极限学习机 (DFRTELM)算法的导数函数，并利用该算法构建了煤炭特征分析模型。DOI: 101016/jsaa2022 Corpus ID: ; Coal identification based on a deep network and reflectance spectroscopy @article{Xiao2022CoalIB, title={Coal identification based on a deep network and reflectance spectroscopy}, author={Dong Xiao and Thi Tra Giang Le and Trung Thanh Doan and Ba Tuan Le}, journal={Spectrochimica actaCoal identification based on a deep network and reflectance To establish an environmentally benign method for the phenolic compounds separation from coal liquefaction oil, deep eutectic solvents (DES) as a green alternative to traditional solvent have been Wenying LI Professor Doctor of Philosophy ResearchGate2021年12月1日 Deep learning is an effective way to improve the classification accuracy of coal images for the machine visionbased coal sorting However, the related research on deep learningbased mineral Deep learningbased image classification for online multicoal
Wencong Xiao dblp
Huazhi Xu, Xiaoyan Luo, Wencong Xiao: Multiresidual unit fusion and Wasserstein distancebased deep transfer learning for mill load recognition Signal Image Video Process Elastic Scaling of Training Data PreProcessing Pipelines for Deep Learning Proc ACM Manag Data 1 (2): 193:1193:25 (2023) [c17] view electronic edition via DOI 2020年3月30日 China’s fossil energy is characterized by an abundance of coal and a relative lack of oil and natural gas Developing a strategy in which coal can replace oil and natural gas is, therefore, a necessary and practical approach to easing the excessive external dependence on oil and natural gas Based on the perspective of energy security, this paper proposes a technical Approach and potential of replacing oil and natural gas with coal 2018年11月15日 Herein, we construct a novel electrocatalyst with Fe–Co dual sites embedded in Ndoped carbon nanotubes ((Fe,Co)/CNT), which exhibits inimitable advantages towards the oxygen reduction reaction The electrocatalyst shows stateoftheart ORR performance with an admirable onset potential (Eonset, 115 V vs 1Synergistic effect of welldefined dual sites boosting the DOI: 101016/JTUST2021 Corpus ID: ; Quantitative mechanism of roadway rockbursts in deep extrathick coal seams: Theory and case histories @article{Lianpeng2021QuantitativeMO, title={Quantitative mechanism of roadway rockbursts in deep extrathick coal seams: Theory and case histories}, author={Dai Lianpeng and Pan Quantitative mechanism of roadway rockbursts in deep extrathick coal
Welcome to visit Wei Wei's HomePage
Liangfeng Cheng, Yuchong Hu, Wei Wei and Renzhi Xiao In: The 16th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA'2018), 2018 Deep Representation Learning for Trajectory Similarity Computation [PDF] Xiucheng Li, Kaiqi Zhao, Gao Cong, Christian S Jensen, Wei Wei2015年12月2日 PDF Coals are congenitally deficient as clean energy, 386 Coal Produc tion and Processing Technology The analysis with a Fourier transform infrared (FTIR) spec(PDF) CoalBased Products and Their Uses ResearchGateDOI: 101016/jmicroc2020 Corpus ID: ; Rapid analysis of coal characteristics based on deep learning and visibleinfrared spectroscopy @article{Xiao2020RapidAO, title={Rapid analysis of coal characteristics based on deep learning and visibleinfrared spectroscopy}, author={Dong Xiao and Ba Tuan Le}, journal={Microchemical Journal}, Rapid analysis of coal characteristics based on deep learning and 2019年8月15日 DOI: 101016/JFUEL201904003 Corpus ID: ; Thermokinetic characteristics of coal spontaneous combustion based on thermogravimetric analysis @article{Li2019ThermokineticCO, title={Thermokinetic characteristics of coal spontaneous combustion based on thermogravimetric analysis}, author={QingWei Li and Yang Xiao and Thermokinetic characteristics of coal spontaneous combustion
Wei Li's Homepage
2024年5月16日 Proceedings of EMNLP2018, the 2018 Conference on Empirical Methods in Natural Language Processing [EMNLP 2018] Wei Li, Xinyan Xiao, Yajuan Lyu and Yuanzhuo Wang Improving neural abstractive document Hu WEN Cited by 2,046 of Xi'an University of Science and Technology, Xi’an Read 127 publications Contact Hu WENHu WEN Professor Xi'an University of Science and Technology, 2022年4月5日 Lei et al [10] proposed a method for identifying coal from various origins based on an improved random forest algorithm and nearinfrared spectroscopy Compared with the support vector machine algorithm, the accuracy of their method is improved by 6% Le et al [11] measured coal parameters using a deep learning algorithm and reflection Coal identification based on a deep network and reflectance Yang XIAO, Professor Cited by 3,032 of Xi'an University of Science and Technology, Xi’an Read 133 publications Contact Yang XIAOYang XIAO Professor PhD Xi'an University of Science and
Breakthrough and innovative clean and efficient coal
2021年5月1日 In the past two decades, China’s modern coal chemical industry has made considerable progress, including increasing its overall scale, the demonstration of operationlevel activities of production plants, and specific unit technology (Xie, 2010)However, in adherence to the basic requirements of “clean, lowcarbon, safe and efficient”, the continuous strengthening Wei Li, Chuan Xiao, Yaduo Liu, “LowOrder Auditory Zernike Moment: A Novel Approach for Robust Music Identification in The Compressed Domain”, EURASIP Journal on Advances in Signal Processing (EURASIP JASP), 2013, pp 115 (音频领域权威国际期刊, SCI/EI) 。 64李伟 Welcome to Wei LI's Homepage科研文章 Fudan UniversityZhanKu LI Cited by 1,097 of China University of Mining and Technology, Xuzhou Read 57 publications Contact ZhanKu LIZhanKu LI China University of Mining and Technology, XuzhouXianYong WEI Cited by 12,916 of China University of Mining and Technology, Xuzhou Read 696 publications Contact XianYong WEIXianYong Wei ResearchGate
Rapid analysis of coal characteristics based on deep learning and
2020年9月1日 Spectral analysis has been widely used in the component analysis, grade classification and product qualification [1], [2], [3]For coal mines, many researchers use spectroscopy to analyze the characteristics, types, and composition of coal [4, 5]Cloutis [6] used twodimensional diffuse reflectance spectroscopy to quantify the properties of coalHe found In view of the underground coal mine environment, which uses mostly infrared cameras to sense the surrounding environment’s temperature, the images formed have the problems of less texture information, more noise, and blurred Research on Target Detection in Underground Coal 2021年5月15日 150 kt/a coal tar deep processing project completed and put into operation (Phase II) 2009: Qitaihe Baotailong Coal Chemical Industry Co, Ltd 300 kt/a of coal tar deep processing project started: 2011: Shandong Baoshun Chemical Technology Co, Ltd 2 × 300 kt coal tar deep processing project completed: 2011: Wuhan Iron and Steel (Group) CompanyValueadded utilization of hightemperature coal tar: A reviewDOI: 101016/JINFRARED201807013 Corpus ID: ; Coal analysis based on visibleinfrared spectroscopy and a deep neural network @article{Le2018CoalAB, title={Coal analysis based on visibleinfrared spectroscopy and a deep neural network}, author={Ba Tuan Le and Dong Xiao and Yachun Mao and Dakuo He}, journal={Infrared Physics \ Technology}, Coal analysis based on visibleinfrared spectroscopy and a deep
Coal measure metallogeny: Metallogenic system and implication
2022年5月31日 Coal, coal measure gas, coal conversion to oil and gas, and coalbased new materials are reliable guarantees for stable energy supply and economic and social development in China The coaldominated resource endowment and the economic and social development stage determine the irreplaceable position of coal resources in the energy system Coal 2020年6月1日 Highperformance carbon anodes for sodiumion batteries (SIBs) were synthesized with bituminous coal as precursor through solvent extraction and carbonizationThe solvent extraction endows the coalbased carbon a hierarchical pore structure and enlarged interlayer distance, which can shorten the charge diffusion distance, alleviate the volume Boosting the sodium storage performance of coalbased carbon 2020年6月1日 Boosting the sodium storage performance of coalbased carbon materials through structure modification by solvent extraction Author links open overlay panel Nan Xiao a, Yibo Wei a, Hongqiang Li a, Nan Xiao: Supervision, Project administration Yibo Wei: Project administration, Writing original draft, Formal analysis, Boosting the sodium storage performance of coalbased carbon DOI: 101016/jsaa2022 Corpus ID: ; Rapid proximate analysis of coal based on reflectance spectroscopy and deep learning @article{Xiao2022RapidPA, title={Rapid proximate analysis of coal based on reflectance spectroscopy and deep learning}, author={Dong Xiao and Ze Sheng Yan and Jian Li and Yanhua Fu and ZhenNan Li}, Rapid proximate analysis of coal based on Semantic Scholar
Freeradical thermolysis and hydrogenolysis of model
Freeradical thermolysis and hydrogenolysis of model hydrocarbons relevant to processing of coal Marvin L Poutsma; Cite this: Energy Fuels 1990, 4, 2, 113–131 XiaoQian Yao,, XinJuan Hou,, Haijun Jiao,, HongWei Crude oil cracking in deep reservoirs: A review of the controlling factors and estimation methods Petroleum XiaoLei Zhang, Lei Xie, Eric FoslerLussier, Emmanuel Vincent, “Special issue on advances in deep learning based speech processing,” Neural Networks (NNJ), volume 158, pages 328330, 2023 Jianyu Wang and XiaoLei Zhang, “Deep NMF topic modeling,” Neurocomputing, volume 515, pages 157173, 2023XiaoLei Zhang's Homepage2024年10月1日 Coal is an abundant fossil fuel and has long been one of the world's most valuable sources of energy Based on the genesis, composition, and structural organization, coal can be classified into three major types: anthracite coal, bituminous coal, and lignite [1]During the mining phase, different types of coal are distributed in various strata of the deposit, with Coal type identification with application result quantification Liu et al 49 analysed the mechanism of intensive ventilation of coal dust to prevent coal bursts and its application Xiao et al 50 proposed the ‘overbreakingbolting and 30, and 10 m from fault No 3DF90 were imported into Tecplot software for data processing the method of ‘the coupling destressing of deep coal seamrooffloor A coal seam‐roof‐floor coupling destressing control method of
Scalable processing for realizing 217%efficient all
2022年5月12日 Monolithic allperovskite tandem solar cells show great promise for largescale photovoltaic (PV) applications with the advantage of lowcost solution processing (1–3)However, certified power conversion efficiencies Semantic Scholar extracted view of "Boosting the sodium storage performance of coalbased carbon materials through structure modification by solvent extraction" by Nan Xiao et al Skip to search form Skip to main content Skip to account menu Semantic Fuel Processing Technology 2018; 20Boosting the sodium storage performance of coalbased carbon A modified YOLOv4 model, named GYOLO, for coal gangue recognition is proposed with the aim of reducing model parameters, improving calculation speed, and reducing equipment requirements This paper proposes a modified YOLOv4 model, named GYOLO, for coal gangue recognition with the aim of reducing model parameters, improving calculation speed, and A fast recognition method for coal gangue image processing2022年1月15日 Request PDF A hybrid model for multistep coal price forecasting using decomposition technique and deep learning algorithms Accurate and reliable coal price prediction is of great significance A hybrid model for multistep coal price forecasting using
Effect and mechanism of coal gangue concrete modification by
Semantic Scholar extracted view of "Effect and mechanism of coal gangue concrete modification by basalt fiber" by Mengyu Zhu et al Coal gangue is a byproduct of coal mining and processing, Zixin He Xiao Zhao Meichen Ye Wei Zuo Xiaoxiong Nie Jianjun Zhao Engineering, Environmental Science Sustainability coal processing and utilization low carbon technology coal economics, mine management coal mine environmental impact assessment and control mine rehabilitation, mine closure, etc The Journal is a unique comprehensive academic periodical completely dedicated to the coal science and mining industry in the worldJournal of China Coal Society Ingenta ConnectNVIDIA Research Cited by 2,696 Machine Learning Deep Learning Generative ModelsWeili Nie Google Scholar2020年5月15日 Initially the coal tar was melted on a hot plate and mixed with 60 wt% of freshly reduced Fe/AC catalyst Samples with a typical volume of 35 cm 3 were loaded into the middle zone of the quartz tube reactor (22 cm in length and 1 cm in diameter), then the system was purged with an argon flow at a rate of 167 mLs −1 for 15 min For each test, the sample was The decarbonization of coal tar via microwaveinitiated catalytic deep