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
Research on coal mine safety production prediction model
Coal Mine Safety Evaluation Based on Machine
2022年3月14日 The BP neural network evaluation model is used to analyze and study the intrinsic safety of coal mines, the shortcomings of the intrinsic safety construction of coal mines are found, and then improvement measures are put 2021年8月1日 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 Hybrid CNNLSTM and IoTbased coal mine hazards monitoring 2022年10月1日 This paper aims to study the coal mine safety management index system and environmental risk model based on sustainable operation Based on the coal mine safety Coal mine safety management index system and environmental 2021年3月1日 To investigate the evolutionary mechanisms of coal mine safety systems, and to improve the level of system safety, this paper introduces a new method of assessing and Evolutionary model of coal mine safety system based on multi
Coal mine safety risk prediction by RSSVM combined model
2017年3月1日 The coal mine production safety early warning index system for coal mine gas explosion risk prediction was established from four aspects: personnel, environment,2023年4月24日 In this research, the BP neural network was used and then optimized to build a more efficient and accurate prediction model for the prediction of safety risk factors in the Xiaonan coal mine The BP neural Application of an Optimized PSOBP Neural Network In this paper, we analyze the national coal mine accident records and extract the gas risk impact factors, and extract the causal chain of accidents through Bayesian Network analysis to Research on mine safety situation prediction model: the case of 2022年4月27日 The research shows that the uncertainty prediction model of mining safety production situation overcomes the fuzziness, nonstationarity, and uncertainty of safety Uncertainty prediction of mining safety production situation
Safety Risk Assessment and Risk Prediction in Underground Coal
2021年10月7日 In this study, the hazards occurring in different sections of underground mining have been categorized, and associated risks have been predicted using different machine 2024年9月4日 Combing the complex network theory, a complex network model for the evolution of coal mine safety risks is constructed The key elements that affect coal mine safety risk accidentsResearch on coal mine safety risk evolution and key 2023年3月1日 However, with the development of science and technology, great changes have taken place in the coal mine enterprise production environment, increased number of contributing factors to coal mine safety accidents, and changes to the mine safety management model alone will not achieve a significant improvement in mine safety management, mainly since the Research on coal mine safety management based on digital twin2021年8月1日 This study aims to develop a prediction model using IoT and hybrid CNNLSTM for forecasting underground mine hazards The forecasting model predicts temperature, humidity, and gases based on the sensors' data collected from underground coal mines (Mardonova and Choi, 2018)The prediction model effectively improves safety in the working environment of Hybrid CNNLSTM and IoTbased coal mine hazards monitoring
Prediction of coal mine gas emission based on hybrid machine learning model
2022年11月16日 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) 2024年8月7日 Background As one of the “five major disasters” in coal mines, mine water hazards have become the second largest “killer” after gas accidents in terms of threatening coal mine safety and Time series prediction model using LSTMTransformer neural2015年4月6日 Download Citation Coal mine safety production forewarning based on improved BP neural network Firstly, the early warning index system of coal mine safety production was given from four aspects Coal mine safety production forewarning based on2021年6月30日 Consequently, the grey prediction model is of great significance in ensuring the safety production of coal mine working face and promote the safety management of coal mine(PDF) Research on Prediction Accuracy of Coal Mine Gas
Risk assessment of coal mine water inrush based on PCADBN
2022年1月25日 Therefore, the prediction of coal mine water inrush is a necessary part of coal mine safety production The research and development of coal mine water inrush prediction are based on research on 2020年6月11日 The prediction of roof pressure in mining area plays an important role in effectively preventing roof accidents and ensuring the safety of mine productionRoof Pressure Prediction in Coal Mine Based on Grey Neural 2022年4月1日 Download Citation Identifying coal mine safety production risk factors by employing text mining and Bayesian network techniques Coal industry is a typical highrisk industry with frequent Identifying coal mine safety production risk factors by preventing roof accidents and ensuring the safety of mine production Because the roof pressure in the mine is affected by various natural and human factors, and there is a dynamic and fuzzy Roof Pressure Prediction in Coal Mine Based on Grey
(PDF) Research on the Prediction Method of Monthly Hidden
2022年12月28日 To better prevent the occurrence of hidden dangers of coal mine accidents and ensure the safety production of coal mine enterprises This paper mines and analyses the pattern of historical monthly 2022年4月15日 Over the past 40 years, China’s coal industry has achieved significant progress through comprehensive mechanization From 2016 to 2019, the longterm safety production mechanisms were improved, coal mine mechanization, automation, and intelligence were accelerated, and the efficiency and safety levels were comprehensively enhancedResearch and practice of intelligent coal mine technology 2024年4月9日 reference for future coal mine safety management, this article uses the gray Markov prediction model to develop coal mine accident statistics based on official published data Analytical and predictive research 2 Statistical analysis of coal mine accidents in China from 2012 to 2023 21 Year and level of accidentStatistical analysis of coal mine accidents from 2012 to 2023 and 2021年5月1日 In order to realize coal mine safety production, it is analyzed the importance of geological forecasting in coal mine safety production from three aspects: the close relationship between Research on the Application of Geological Forecast in Coal Mine Safety
Identifying coal mine safety production risk factors by
2022年6月1日 Coal industry is a typical highrisk industry with frequent accidents In an effort to ensure workers’ safety and health, and reduce the probability of productivity decrease, it is essential to identify the contributing factors of coal mine safety production risks through certain technical means2021年5月1日 PDF The key abstract is to use IoT to incorporate a coal mine safety monitoring system The extraction of coal from the field is known as coal mining Find, read and cite all the research Safety Monitoring System in Coal Mine Using IoT ResearchGate2023年5月29日 Reasonable production capacity is related to the economic benefits of an openpit coal mine This study analyzes the relationship between the working face length, the annual advancing speed and Research on production capacity planning method of openpit coal mine 2022年12月29日 Aiming at the problems of the influencing factors of coal mine dust wettability not being clear and the identification process being complicated, this study proposed a coal mine dust wettability identification method based on a back propagation (BP) neural network optimized by a genetic algorithm (GA) Firstly, 13 parameters of the physical and chemical properties of Research on Coal Dust Wettability Identification Based on GA–BP Model
Coal mine safety production forewarning based on improved BP
2015年3月1日 The application of BP neural network to coal mine safety production forewarning system can give full play to nonlinear mapping, selflearning and selfadaption ability of artificial neural network [18]It improves BP neural network by using intelligent optimization algorithms so as to avoid the weakness of falling into local minimum and slow convergence speed2020年10月30日 PDF Coal and gas outburst has been one of the main threats to coal mine safety Accurate coal and gas outburst prediction is the key to avoid Find, read and cite all the research you need RealTime Prediction Model of Coal and Gas Outburst2024年1月25日 The traditional methods for identifying water sources in coal mines lack the ability to quickly detect water sources and are prone to causing secondary pollution of samples In contrast, laser induced fluorescence (LIF) technology has been introduced for the identification of coal mine water sources due to its high sensitivity and realtime performance However, A Mine Water Source Prediction Model Based on LIF Technology Coal mine safety management is the foundation and decisive factor of coal mining The manual detection model is the main way for traditional coal mine safety management, which has problems such as inefficient identification of Research on coal mine safety management based on
(PDF) Prediction of Coal Mine Accidental Deaths for 5
2020年7月1日 PDF The situation of coal mine safety production is grim, in order to emphasize the importance of miners’ safety, this paper predicted the death toll Find, read and cite all the research 2024年2月22日 The safety of mining has always been a concern The occurrence of safety accidents not only endangers human health, but also causes serious damage to the ecological environment With the continuous upgrade and improvement of mining technology, most mines are undergoing intelligent construction and transformation In order to analyze security risks Intelligent mine safety risk based on knowledge graph: hotspots 2014年3月1日 Download Citation Simulation study of coal mine safety investment based on system dynamics To generate dynamic planning for coal mine safety investment, this study applies system dynamics to Simulation study of coal mine safety investment based on2023年4月24日 Therefore, this research aimed to develop an efficient model for assessing and predicting safety risk factors in underground mines using existing data from the Xiaonan coal mine A model for evaluating safety risks in underground coal mines was developed based on the optimized particle swarm optimizationbackpropagation (PSOBP) neural networkApplication of an Optimized PSOBP Neural Network to the
Research on coal mine safety management based on digital twin
2023年2月1日 Coal mine safety management is the foundation and decisive factor of coal mining The manual detection model is the main way for traditional coal mine safety management, which has problems such as 2020年2月20日 holds 15 utility model patents His research (GRU)based mine gas concentration prediction model is Gas disaster is one of the most serious disasters in coal mine safety productionResearch on a Mine Gas Concentration Forecasting Model Based on DOI: 101155/2022/ Corpus ID: ; Research on the Prediction Model of Mine Subsidence Based on ObjectOriented and Probability Integration Method @article{Gu2022ResearchOT, title={Research on the Prediction Model of Mine Subsidence Based on ObjectOriented and Probability Integration Method}, author={Zhongyuan Gu and [PDF] Research on the Prediction Model of Mine Subsidence 2023年3月1日 However, with the development of science and technology, great changes have taken place in the coal mine enterprise production environment, increased number of contributing factors to coal mine safety accidents, and changes to the mine safety management model alone will not achieve a significant improvement in mine safety management, mainly since the Research on coal mine safety management based on digital twin
Hybrid CNNLSTM and IoTbased coal mine hazards monitoring
2021年8月1日 This study aims to develop a prediction model using IoT and hybrid CNNLSTM for forecasting underground mine hazards The forecasting model predicts temperature, humidity, and gases based on the sensors' data collected from underground coal mines (Mardonova and Choi, 2018)The prediction model effectively improves safety in the working environment of 2022年11月16日 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) Prediction of coal mine gas emission based on hybrid machine learning model2024年8月7日 Background As one of the “five major disasters” in coal mines, mine water hazards have become the second largest “killer” after gas accidents in terms of threatening coal mine safety and Time series prediction model using LSTMTransformer neural2015年4月6日 Download Citation Coal mine safety production forewarning based on improved BP neural network Firstly, the early warning index system of coal mine safety production was given from four aspects Coal mine safety production forewarning based on
(PDF) Research on Prediction Accuracy of Coal Mine Gas
2021年6月30日 Consequently, the grey prediction model is of great significance in ensuring the safety production of coal mine working face and promote the safety management of coal mine2022年1月25日 Therefore, the prediction of coal mine water inrush is a necessary part of coal mine safety production The research and development of coal mine water inrush prediction are based on research on Risk assessment of coal mine water inrush based on PCADBN2020年6月11日 The prediction of roof pressure in mining area plays an important role in effectively preventing roof accidents and ensuring the safety of mine productionRoof Pressure Prediction in Coal Mine Based on Grey Neural 2022年4月1日 Download Citation Identifying coal mine safety production risk factors by employing text mining and Bayesian network techniques Coal industry is a typical highrisk industry with frequent Identifying coal mine safety production risk factors by