Research on the Strong Generalization of Coal Gangue Recognition Technology Based on the Image and Convolutional Neural Network under Complex Conditions. [PDF]
ACS Omega, 2023 Xun Q, Yang Y, Liu Y.
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An intelligent coal gangue recognition method based on improved YOLOv12
Gong-kuang zidonghuaTo address the difficulty of accurately and efficiently recognizing coal gangue caused by complex environmental factors such as high dust concentration and highly variable illumination in mines, this study improved the YOLOv12 network model and proposed ...
ZHOU Wei, LI Guangke
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Application of Hilbert-Huang Transform to Vibration Signal Analysis of Coal and Gangue
, 2010 In this paper, a new method of vibration signal analysis of coal and gangue based on Hilbert-Huang transform is presented. Empirical mode decomposition algorithm was used to decompose the original vibration signal of coal and gangue into the intrinsic ...
Wei Liu
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Coal gangue identification method based on SDSE-YOLO in complex operating conditions
Meitan kexue jishuThis study addresses the technical challenges of coal gangue detection algorithms during separation in coal mines, such as low recognition accuracy, missed detections and false positives in complex conditions involving uneven brightness distribution ...
Jun ZHANG +6 more
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Gong-kuang zidonghua, 2013 In view of problems that γ ray method is not suitable for working face with no or little radioactive elements in roof and radar detection method has little detection range and serious signal attenuation which were used in current coal and gangue ...
HE Ai-xiang +3 more
doaj
DEL_YOLO: A Lightweight Coal-Gangue Detection Model for Limited Equipment
The gangue mixed in raw coal has small feature differences from coal, in order to solve the existing gangue recognition, methods generally have slow detection speed and are difficult to deploy at the edge end of the problem, a lightweight gangue target ...
Mengxu Guo +4 more
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Research on coal gangue recognition method based on CED-YOLOv5s model
Gong-kuang zidonghuaDue to the complex working conditions of high noise, low illumination, and blurred movement in coal mines underground, as well as the phenomenon of coal gangue easily gathering, it is difficult to extract features from coal gangue object detection models. The classification and positioning of coal gangue are inaccurate.
HE Kai +5 more
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Multiclass Classification of Coal Gangue Under Different Light Sources and Illumination Intensities
As a solid mixture discharged during coal production, coal gangue possesses comprehensive utilization potential. Efficient sorting and pre-enrichment of its classification are crucial for green mining practices.
Weinong Liang +6 more
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To address the low recognition accuracy of models for coal gangue images in intelligent coal preparation systems—especially in identifying small target coal gangue due to factors such as camera angle changes, low illumination, and motion blur—
Yurong Yue, Wei Shan, Guilin Zong
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A deep learning method based on multi-scale fusion for noise-resistant coal-gangue recognition. [PDF]
Sci RepSong Q +5 more
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