The process of coal mining generates high amounts of coal gangue. Accordingly, coal-gangue separation is a key problem limiting coal production and quality. Terahertz time-domain spectroscopy was combined with multivariate statistical analyses to identify different kinds of coal and gangue. First, the terahertz spectrum and power spectrum of the …
Sun and Chen [] decomposed coal rock images based on double-tree complex wavelet transform and completed image identification based on relative entropy similarity.Li et al. [] built a coal gangue sorting image capture system, and the test results of coal and gangue classification accuracy were 90.3% and 83.0%, respectively.Xue …
For the traditional machine learning methods rely on manual experience and deep learning classification model depth and complex structure, resulting in poor gangue classification performance, this paper proposes a coal gangue recognition method (CNN-SVM) based on the combination of convolutional neural network (CNN) and support …
Therefore, in order to decrease misplacement effects and improve the classification sharpness of coal slime, it is very crucial to study the classification mechanism of coal and gangue particles. However, coal slime is a multi-component system and its highly variable gangue composition and particle size distribution create …
For coal and gangue, intelligent sorting processes for separation, the use of coal and gangue mineral components with different fundamental differences, and the study of different properties of …
For the first class (Al/Si < 0.3), the main components of coal gangue are quartz and feldspar, and the plasticity is poor because of little clay mineral and large …
Computer vision-based separation methods for coal gangue face challenges due to the harsh environmental conditions in the mines, leading to the reduction of separation accuracy.
To detect coal content in gangue, a novel approach based on image analysis and particle swarm optimization–support vector machine (PSO-SVM) was presented. ABSTRACT To detect coal content in gangue, a novel approach based on image analysis and particle swarm optimization–support vector machine (PSO-SVM) …
Coal gangue is one of China's main industrial solid wastes, which contains various harmful heavy metal elements, such as lead (Pb). The long-term accumulation of coal gangue causes Pb to migrate to the surrounding environment due to weathering and rain erosion, eventually endangering human life and health with its continuous …
This paper provides a low-cost and highly reliable method for coal and gangue classification as well as facilitating the automation of coal and gangue classification and high-quality allocation of fossil …
The precise classification of coal and gangue is a crucial link for effective sorting and efficient utilization. However, there are some shortcomings in traditional methods, such as water ...
In this paper, an intelligent identification method of gangue based on polarization imaging technology is proposed. Firstly, a gangue image acquisition system was built in the laboratory, and 2000 groups of coal and gangue samples were collected, including polarization intensity images, polarization angle images and polarization …
Dou Dongyang et al. used a relief-SVM to filter out characteristic attributes that can effectively distinguish coal and gangue based on coal and gangue images …
Coal gangue is one of the largest mine solid wastes in China, and its discharge and stockpiling have caused resource waste, environmental pollution and other problems. Starting from the resource …
Pengcheng Yan 15 proposed an intelligent classification method for coal gangue using multispectral imaging technology and object detection. This method achieved a static recognition accuracy of 98 ...
M S Alfarzaeai et al. [2], also addressed the use of thermal images with convolutional neural network to perform coal gangue recognition, the results showed that using thermal images lead to immunity against coal gangue classification issues such as visual appearance similarities, dust, light intensity, and source heterogeneity, results came ...
A supervised classification method using support vector machines (SVM) was used to recognize coal and gangue, and the evaluation of classification accuracy shows that more than 82% of the pixels can be correctly classified, and this study provides strong support for the visual sensors with complete spectral band combinations to …
CLASSIFICATION METHOD OF COAL AND GANGUE USING TERAHERTZ TIME-DOMAIN SPECTROSCOPY, CLUSTER ANALYSIS AND PRINCIPAL COMPONENT ANALYSIS D. Shao,a Sh. Miao,a,* Q. Fan,a X. Wang,a UDC 543.42:622.33 Zh. Liu,b,c and E. Dingb,c The process of coal mining generates high amounts of coal gangue. …
DOI: 10.2139/ssrn.4281797 Corpus ID: 253754424; Coal and Gangue Classification in Actual Environment of Mines Based on Deep Learning @article{Luan2023CoalAG, title={Coal and Gangue Classification in Actual Environment of Mines Based on Deep Learning}, author={Hengxuan Luan and Haoliang Xu and Wei-Feng Tang and Ying Tian …
Top coal caving is a process for the rational extraction of large amounts of coal resources. However, this process readily causes release of excessive amounts of gangue during the coal release process. The conventional technique, which involves visual inspection, is not only labor-intensive but also can introduce inaccuracies. Coal and …
A coal gangue recognition method (CNN-SVM) based on the combination of convolutional neural network (CNN) and support vector machine (SVM) is proposed, which has obvious advantages compared with traditional classification models and classical classification models, and the recognition speed is faster compared with the …
Observing coal features is the first step in learning about coal. Here, a coal gangue detection system was created that enables users to do a search even when they are unsure of the coal's name by looking at specific coal features. Currently, machine vision is used to extract and analyze color, size, shape, and surface texture in coal classification. Even …
The process of coal mining generates high amounts of coal gangue. Accordingly, coal–gangue separation is a key problem limiting coal production and …
Coal gangue image recognition is a critical technology for achieving automatic separation in coal processing, characterized by its rapid, environmentally friendly, and energy-saving nature. However, the response characteristics of coal and gangue vary greatly under different illuminance conditions, which poses challenges to the stability of …
This study achieves the classification of coal and gangue based on their mass, volume, and weight. A dataset of volume, weight and 3_side images is …
The early fusion network can complete the coal gangue classification target task faster and better than the late fusion network. To further analyze the recognition and classification effect of coal gangue, the confusion matrix is used for visual analysis, and the results are shown in Fig 17. As shown in the figure, the total number of samples ...
The precise classification of coal and gangue is a crucial link for effective sorting and efficient utilization. However, there are some shortcomings in traditional methods, such as water consumption, coal slime pollution, and great influence of environmental factors, and so on.
Furthermore, the study identifies the 959.37 nm band as optimal for coal and gangue classification. Compared to existing super-resolution methods, ANIMR-GAN offers advantages, paving the way for ...
ABSTRACT Coal and gangue recognition is a key issue in rock picking during the coal preparation process. Four operating conditions including raw coal with the dry clean surface, wet clean surface, dry surface covered by slime and wet surface covered by slime are frequently encountered in real applications. The Relief-SVM method was presented …
To address the lightweight and real-time issues of coal sorting detection, an intelligent detection method for coal and gangue, Our-v8, was proposed based on improved YOLOv8. Images of coal and gangue with different densities under two diverse lighting environments were collected. Then the Laplacian image enhancement algorithm …
Request PDF | On Feb 1, 2023, Hengxuan Luan and others published Coal and gangue classification in actual environment of mines based on deep learning | Find, read and cite all the research you ...
This paper proposes a simple and efficient method based on infrared spectroscopy to simultaneously achieve coal gangue classification and coal type identification.
