Results 1 to 10 of about 4,745 (178)

PCViT: A Pre-Convolutional ViT Coal Gangue Identification Method

Energies, 2022
For the study of coal and gangue identification using near-infrared reflection spectroscopy, samples of anthracite coal and gangue with similar appearances were collected, and different dust concentrations (200 ug/m3, 500 ug/m3 and 800 ug/m3), detection distances (1.2 m, 1.5 m and 1.8 m) and mixing gangue rates (one-third coal, two-thirds coal, full ...
Jianjian Yang, Boshen Chang, Yuzeng Zhang, Yucheng Zhang, Wenjie Luo   +4 more
doaj   +6 more sources

A Coal Gangue Identification Method Based on HOG Combined with LBP Features and Improved Support Vector Machine

Symmetry, 2023
Identification of coal and gangue is one of the important problems in the coal industry. To improve the accuracy of coal gangue identification in the coal mining process, a coal gangue identification method based on histogram of oriented gradient (HOG) combined with local binary pattern (LBP) features and improved support vector machine (SVM) was ...
Gang Cheng, Jie Chen, Yifan Wei, Sensen Chen, Zeye Pan   +4 more
exaly   +4 more sources

Study on Coal Gangue Identification Based on Vibration and Its Adaptability to Coal-Caving Process Parameters

Shock and Vibration, 2023
The broken top coal and gangue in the fully mechanized cave mining will be released from the rear of the hydraulic support in the form of bulk. In this process, the medium properties through the coal opening can be judged by monitoring the vibration signal on the tail beam.
Lirong Wan, Jiantao Wang, Dejian Ma, Zhaoji Li, Zhenguo Lu, Zhaosheng Meng   +5 more
doaj   +3 more sources

RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification. [PDF]

Sensors (Basel)
Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. In response to the above, this article proposes a new “hardware friendly” coal gangue image recognition algorithm, RRBM-YOLO, which is combined with dark ...
Wang Y, Kou Z, Han C, Qin Y.
europepmc   +5 more sources

Dielectric identification method and system design of coal gangue based on frequency shift characteristics. [PDF]

Sci Rep
This paper investigates the impact of variations in excitation frequency variations on the dielectric properties of coal gangue to enhance identification accuracy in challenging underground conditions. A dielectric identification methodology based on frequency shift characteristics is proposed, focusing on coal gangue samples collected from Zhujidong ...
Wang X, Wu M, Zhao P.
europepmc   +4 more sources

Experimental study on microwave propagation characteristics of different coal-gangue mixtures [PDF]

Meitan kexue jishu, 2023
The problem of coal-gangue identification is one of the technical problems that have not been effectively solved for a long time in the coal industry. By analyzing the characteristics and limitations of existing coal-gangue identification methods, the ...
Lei SI, Jiahao LI, Feng XING, Dong WEI, Jianbo DAI, Zhongbin WANG   +5 more
doaj   +2 more sources

A multi modal fusion coal gangue recognition method based on IBWO-CNN-LSTM. [PDF]

Sci Rep
Accurate identification of coal and gangue is a crucial guarantee for efficient and safe mining of top coal caving face. This article proposes a coal-gangue recognition method based on an improved beluga whale optimization algorithm (IBWO), convolutional
Hao W, Jiang H, Song Q, Song Q, Sun S.
europepmc   +3 more sources

Design and application of coal gangue sorting system based on deep learning. [PDF]

Sci Rep
With the advancement of science and technology, coal-washing plants are transitioning to intelligent, information-based, and professional sorting systems.
Zhang K, Wang Z, Zhang Z, Shi Z, Qi Y, Du M, Chen Y, Liu T, Chen Y, Yin Z.   +9 more
europepmc   +3 more sources

Coal gangue recognition based on spectral imaging combined with XGBoost.

PLoS ONE, 2023
The identification of coal gangue is of great significance for its intelligent separation. To overcome the interference of visible light, we propose coal gangue recognition based on multispectral imaging and Extreme Gradient Boosting (XGBoost).
Minghao Zhou, Wenhao Lai
doaj   +3 more sources

A coal-gangue optimization identification method

Gong-kuang zidonghua, 2020
Aiming at problem that target detection of coal-gangue image is not accurate due to wear of conveyor belt, which affects identification accuracy of coal-gangue, a coal-gangue optimization identification method is proposed. After pre-processing of collected images such as cutting, denoising and grayscale, the trained cornernet-squeeze deep learning ...
ZHAO Minghui
openaire   +3 more sources