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
Small gangue selection machine
Design and application of coal gangue sorting system
2024年7月17日 Traditional manual gangue picking and multiaxis robotic arm gangue selection currently suffer from low recognition accuracy, slow sorting efficiency, and high worker labor intensity This2023年5月28日 The current target detection of gangue using deep learning is similar in size to that of coal blocks, with a size greater than 50mm, which is limited by the low visibility and Improved YOLOv7 Network Model for Gangue Selection Robot for 2023年5月28日 To address these issues, this study proposes an improved method for detecting gangue and foreign matter in coal, utilizing a gangue selection robot with an enhanced YOLOv7 network modelImproved YOLOv7 Network Model for Gangue This study addresses the issues of slow gangue selection speed and low recognition accuracy in gangue selection machine methods To overcome these challenges, an improved gangue and Improved YOLOv7 Network Model for Gangue Selection Robot for
Improved foreign object tracking algorithm in coal for belt
2024年3月31日 The objective is to combine the coal foreign object detection and tracking stages to achieve accurate detection and tracking of foreign objects by the belt conveyor gangue 2024年2月23日 To address the issues of complex algorithm models, poor accuracy, and low realtime performance in the coal industry's coal gangue sorting, a lightweight realtime The realtime detection method for coal gangue based onCIoU bounding box regression loss and the Kmeans++ clustering anchorbox are used to improve the detection accuracy of targets Experimental equipment was built, and coal gangue datasets of small size, large size, dim light, mutual Coal gangue detection and recognition method based The automatic sorting of coal gangues can be realized by the machine vision based on sorting technology and the mechanical arms As a result, the production cost can be effectively Intelligent Sorting System of Coal Gangue with Machine Vision
Intelligent Gangue Sorting System Based on Dual
2023年12月21日 To tackle the challenges associated with coal gangue target detection, including algorithm performance imbalance and hardware deployment difficulties, in this paper, an intelligent gangue separation system that adopts 2024年11月16日 The efficient separation of coal and gangue remains a critical challenge in modern coal mining, directly impacting energy efficiency, environmental protection, and sustainable development Current machine visionbased sorting methods face significant challenges in dense scenes, where label rewriting problems severely affect model Coal and Gangue Detection Networks with Compact and HighTraditional methods for gangue selection in coal processing include manual gangue selection, jigging gangue selection, heavy media gangue selection, and ray gangue selection [33] Manual gangue separation is characterized by high labor intensity and low efficiency Jigging gangue selection offers a simple process, ease of operation, and goodImproved YOLOv7 Network Model for Gangue Selection Robot for Gangue 2016年5月27日 Guest contributor: Tim Anderson, Stober Selecting a gearbox can be quite difficult Customers have a variety of gearboxes to choose from that are capable of fulfilling diverse requirements A wrong decision could result in Basics of Gearbox Selection Machine Geeks
Research on light weight intelligent identification method of coal
China's coal gangue sorting has developed from manual gangue selection to mechanized gangue selection, automated gangue selection, and then to the direction of intelligent gangue selection (Shang et al 2024) The key of intelligent separation of coal gangue is to identify coal gangue accurately and quickly2023年5月28日 You are accessing a machinereadable page In order to be humanreadable, Improved YOLOv7 Network Model for Gangue Selection Robot for Gangue and Foreign Matter Detection in Coal Sensors 2023, 23(11), where small gangue blocks were mixed in the coal pile above the conveyor beltImproved YOLOv7 Network Model for Gangue Selection Robot for Gangue 2023年2月1日 Coal Gangue Detection and Recognition Method Based on Multi‐scale Fusion Lightweight Network SMS‐YOLOv3Coal Gangue Detection and Recognition Method Based on 2005年9月18日 Download Citation Coal gangue online recognition and automation selection system based on ARM and CAN bus ARM (advanced RISC machines) microcontroller is widely used in lots of fields with Coal gangue online recognition and automation selection system
(PDF) Machine selection for custom manufacturing in smallscale
2023年7月18日 In this context, the issue of machine selection for smallscale enterprises that make ordertype production , based on the principle that a rational investment goes through the selection of the 2024年10月23日 Comments 4: Add a specialized 160 × 160 small target detection head to enhance detection accuracy for small coal gangue targets, often missed due to poor illumination or motion blur Response 4: Thank you for pointing this out We have included a description of the 160 × 160 small target detection head in lines 251 to 258 of the articleElectronics Free FullText Optimization Study of Coal Gangue2024年10月30日 Given that small coal gangue poses a lesser threat to safety, this study primarily focuses on gangue and large coal lumps with diameters not less than 50 mm To verify the performance and processing speed of the AMCFDN model in detecting foreign objects in coal flow, this paper compares its detection results with other commonly used semisupervised and AMCFDN: semisupervised anomaly measurebased coal flow2023年1月26日 Distribution of data representation forms in the reviewed papers As shown in Figure 2, the number of papers that utilized the crisp data form in the recent machine selection literature is almost (PDF) MultiCriteria DecisionMaking for Machine
Coal gangue detection and recognition algorithm based on
the accuracy and efficiency of detecting and recognising smallsize coal and gangue and improves environmental robustness Furthermore, ing environments, and its efficiency is low; mechanical gangue selection, such as screen jigging, heavy medium and flotation, vector machine model through the texture characteristics of2024年7月17日 Traditional manual gangue picking and multiaxis robotic arm gangue selection currently suffer Small air quantities fail to of graphical user interfaces for machine vision Design and application of coal gangue sorting system machine learning have also been widely studied and utilized algorithm meets the accuracy and realtime requirements of coal gangue small gangue selection No water, high recognition rateCoal Gangue Detection and Recognition Method Based on Multi 2023年5月28日 An improved method for detecting gangue and foreign matter in coal, utilizing a gangue selection robot with an enhanced YOLOv7 network model and incorporating a dual path attention mechanism is proposed Coal production often involves a substantial presence of gangue and foreign matter, which not only impacts the thermal properties of coal and but also Improved YOLOv7 Network Model for Gangue Selection Robot for Gangue
Selecting the Correct Industrial Machine Vision Camera
However, unlike typical machine vision cameras used for small businesses and shops, cameras for industrial applications are more robust and can withstand harsh environmental conditions Additionally, industrial machine vision cameras can capture a higher number of images per second and send that data directly to the machine vision system for processing2021年5月27日 To detect coal content in gangue, a novel approach based on image analysis and particle swarm optimization–support vector machine (PSOSVM) was presented ABSTRACT To detect coal content in gangue, a novel approach based on image analysis and particle swarm optimization–support vector machine (PSOSVM) was presented First, 15 features that Detection of coal content in gangue via image analysis and 2023年12月1日 Feature selection has been a crucial area of research in machine learning for many years In this field, a feature is a measure that describes relevant and discriminative information about a data object []Selecting the right features is a critical step in building a machine learning model, as it can significantly improve the model's performance, reduce its Feature selection techniques for machine learning: a survey of 2021年5月21日 As a dimensionality reduction technique, feature selection aims to choose a small subset of the relevant features from the original features by removing irrelevant, redundant, or noisy featuresFeature Selection — Exhaustive Overview by Danny Butvinik
The realtime detection method for coal gangue based on
2024年2月23日 To address the issues of complex algorithm models, poor accuracy, and low realtime performance in the coal industry's coal gangue sorting, a lightweight realtime detection method called YOLOv8sGSC is proposed based on the characteristics of coal gangue This method incorporates the ghost module into the YOLOv8s backbone network to reduce the Download Citation On Sep 1, 2024, Yongxin Li and others published Prediction of coal gangue volcanic ash activity based on machine learning Find, read and cite all the research you need on Prediction of coal gangue volcanic ash activity based on machine 2024年3月31日 In this paper, the YOLOv7 and DeepSORT algorithms have been enhanced for foreign object tracking in coal for belt conveyor gangue selection robots The objective is to combine the coal foreign object detection and tracking stages to achieve accurate detection and tracking of foreign objects by the belt conveyor gangue selection robotImproved foreign object tracking algorithm in coal for belt 2024年7月23日 Focusing on the issues of complex models, high computational cost, and low identification speed of existing coal gangue image identification object detection algorithms, an optimized YOLOv5s lightweight detection model for coal gangue is proposed Using ShuffleNetV2 as the backbone network, a convolution pooling module is used at the input end instead of the Lightweight detection model for coal gangue identification based
(PDF) Coal gangue detection and recognition algorithm based on
2021年9月8日 Focusing on various problems in coal gangue detecting and recognising algorithms, such as limited receptive field, slow convergence rate and low accuracy of small particle recognition, this paper 2024年1月1日 DOI: 101016/jmeasurement2024 Corpus ID: ; Improved foreign object tracking algorithm in coal for belt conveyor gangue selection robot with YOLOv7 and DeepSORT @article{Yang2024ImprovedFO, title={Improved foreign object tracking algorithm in coal for belt conveyor gangue selection robot with YOLOv7 and DeepSORT}, Improved foreign object tracking algorithm in coal for belt 2021年9月8日 Coal and gangue samples with diameters of 4–6 and 10–12 cm were tested In the SSD network, the detection of the small coal and gangue samples under different light intensities was poor, with the detection being correct only when the light intensity was 599 luxCoal gangue detection and recognition algorithm based on 2022年12月5日 The five different illuminance involved in this experiment were 3790, 11,310, 17,130, 23,500 and 31,070 Lux, respectively A total of 1800 coal and gangue images after graying were obtained in the Image feature extraction and recognition model construction of
Study on the macro–micro evolution of compaction Nature
2024年2月28日 Tests on the basic properties of gangue materials As shown in Fig 2, the composition of gangue was analysed by RXD spectroscopy in this experimentThe experimental results show that the main 2024年1月11日 The recognition technology of coal and gangue is one of the key technologies of intelligent mine construction Aiming at the problems of the low accuracy of coal and gangue recognition models and the difficult recognition of smalltarget coal and gangue caused by lowillumination and highdust environments in the coal mine working face, a coal and gangue Research on Coal and Gangue Recognition Based on the Recognition and sorting of coal and gangue based on image process and multilayer perceptron Junhao Jiang a, Yanfeng Han , Huijun Zhaob, Jianli Suoc, and Qinbao Cao aCollege of Mechanical and Recognition and sorting of coal and gangue based on image 2023年2月23日 Aiming at the problems of large memory footprint, low detection speed, and low detection accuracy for small and overlapping targets existing in the current coal gangue target detection algorithm (PDF) Coal gangue detection and recognition method based on
Coal gangue detection and recognition algorithm based on
Received: 3 June 2021 Revised: 25 August 2021 Accepted: 29 August 2021 IET Image Processing DOI: 101049/ipr212339 ORIGINAL RESEARCH PAPER Coal gangue detection and recognition algorithm based onThe automatic sorting of coal gangues can be realized by the machine vision based on sorting technology and the mechanical arms so that the production cost can be effectively reduced while the coal sorting efficiency is greatly improved Gangue sorting is an important part of coal production, which is to choose gangues from coal blocks At present, most of the separation of Intelligent Sorting System of Coal Gangue with Machine Vision2020年8月18日 Feature selection is the process of identifying and selecting a subset of input variables that are most relevant to the target variable Perhaps the simplest case of feature selection is the case where there are numerical input variables and a numerical target for regression predictive modeling This is because the strength of the relationship between []How to Perform Feature Selection for Regression Data2023年11月11日 Coal gangue image recognition is a critical technology for achieving automatic separation in coal processing, characterized by its rapid, environmentally friendly, and energysaving nature However, the response characteristics of coal and gangue vary greatly under different illuminance conditions, which poses challenges to the stability of feature extraction Research on Recognition of Coal and Gangue Based on Laser
Intelligent photoelectric identification of coal and gangue − A
2024年6月30日 Artificial gangue selection, as the earliest method of coal gangue separation, exhibits low efficiency and accuracy while also posing health risks to workers [10]Wet gangue selection technology utilizes the gravity difference between coal and gangue in a liquid medium to achieve efficient separation, addressing the issue of fly ash that endangers worker health [11]With the development of deep learning technology in recent years, 22, 23 deep learningbased target detection is used in the field of gangue detection, 2426 boasting advantages over traditional machine learning methods in terms of no manual feature selection, excellent feature expression capability, and excellent detection accuracy 27, 28 Deep learning technology can Coal gangue detection and recognition method based on 2022年2月3日 Machine learning methods have been used in multifactor stock strategy for years This paper uses three machine learning methods and linear regression method to find the most appropriate approachMultifactor Stock Selection Strategy Based on Machine Learning The existing deep learning based foreign object detection models for conveyor belts are relatively large and difficult to deploy on edge devices There are errors and omissions in detecting foreign objects of different sizes and small objects In order to solve the above problems, a foreign object detection method for coal mine conveyor belts based on improved YOLOv8 is proposed The Foreign object detection of coal mine conveyor belt based on
Prediction of Calorific Value for Coal Gangue Based on the Machine
gangue based on PSOSVR proposed in this study has high prediction accuracy and convergence speed, which can provide scientific basis for energy utilization of coal gangue Keywords: Coal Gangue, Calorific Value Prediction, Support Vector Regression, Particle Swarm Optimization, Machine Learning Algorithm 1 Introduction