Results 31 to 40 of about 381 (161)

Coal-gangue image recognition in fully-mechanized caving face based on random forest

Gong-kuang zidonghua, 2020
Aiming at problems of high difficulty in parameter adjustment, low prediction accuracy and easy over-fitting in present coal-gangue image recognition methods in fully-mechanized caving face, a coal-gangue image recognition method in fully mechanized ...
XUE Guanghui, LI Xiuying, QIAN Xiaoling, ZHANG Yunfei   +3 more
doaj   +1 more source

Fast recognition using convolutional neural network for the coal particle density range based on images captured under multiple light sources

International Journal of Mining Science and Technology, 2021
A method based on multiple images captured under different light sources at different incident angles was developed to recognize the coal density range in this study.
Feiyan Bai, Minqiang Fan, Hongli Yang, Lianping Dong   +3 more
doaj   +1 more source

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 ...
Jianjian Yang, Boshen Chang, Yuzeng Zhang, Yucheng Zhang, Wenjie Luo   +4 more
doaj   +1 more source

Design of photometric separation system for coal and gangue

Gong-kuang zidonghua, 2013
In view of requirements of underground separation and backfilling and utilization for coal and gangue, the paper proposed a design scheme of photometric separation system for coal and gangue based on laser 3D scanning and dynamic weighing.
WANG Wei-dong, ZHANG Chen, MA Zhong-liang, CAO Chun-xiao, WANG Tong-tong, ZHANG Lu-qi, REN Chun-xing, LIANG Jing   +7 more
doaj   +1 more source

Research on Coal and Gangue Recognition Model Based on CAM-Hardswish with EfficientNetV2

Applied Sciences, 2023
In response to the multiscale shape of coal and gangue in actual production conditions, existing coal separation methods are inefficient in recognizing coal and gangue, causing environmental pollution and other problems.
Na Li, Jiameng Xue, Sibo Wu, Kunde Qin, Na Liu   +4 more
doaj   +1 more source

Coal gangue recognition method based on water heat transfer and infrared thermal imaging

Gong-kuang zidonghua
The coal gangue recognition method based on visible light images has low accuracy and slow recognition speed. The coal gangue recognition method based on high-energy ray transmission has significant radiation, resulting in limited application.
CHENG Gang, CHEN Jie, PAN Zeye, WEI Yifan, CHEN Sensen   +4 more
doaj   +1 more source

Mechanism and disaster control new technology of strong ground pressure manifestation in ultra‐large mining face

Deep Underground Science and Engineering, EarlyView.
In response to the problem of strong mining pressure manifestation along the goaf roadway in a thick coal seam mining area, this study uses a new type of combined blasting roof cutting technology to effectively control the manifestation and deformation of mining pressure along the goaf roadway.
Xiaoding Xu, Manchao He, Jun Yang, Yubing Gao, Qiang Fu, Qing Ma, Yajun Wang   +6 more
wiley   +1 more source

Modeling the Thermal Properties of Hydrogen‐Based Direct Reduced Iron Using Computational Thermodynamics and Machine Learning

steel research international, EarlyView.
Hydrogen‐based direct reduced iron (H‐DRI) melts differently from scrap and carbon‐bearing DRI. This work combines differential scanning calorimetry experiments, FactSage thermodynamics, and simple composition‐based regression to predict solidus, liquidus, heat capacity, and enthalpy for H‐DRI.
Ankur Agnihotri, Petri Sulasalmi, Pasquale Cavaliere, Ville‐Valtteri Visuri   +3 more
wiley   +1 more source

Coal and gangue recognition research based on improved YOLOv5

Gong-kuang zidonghua, 2022
The existing deep learning-based coal and gangue recognition methods are prone to false detection and missed detection when applied to underground complex environments. The recognition precision of small target coal and gangue is low. In order to solve this problem, an improved YOLOv5 model is proposed, and coal and gangue recognition is realized based
ZHANG Shiru, HUANG Zongliu, ZHANG Yuanhao, ZHANG Ao, JI Liang   +4 more
openaire   +1 more source

Influence of an Electromagnetic Field on Direct Reduction of Iron Oxide Using Hydrogen as a Reducing Agent

steel research international, EarlyView.
This study investigates the reduction of pure iron oxides and industrial iron ore using hydrogen gas as a reducing agent. Additionally, to determine whether the reduction process can be accelerated, electromagnetic fields of 50 Hz and 25 kHz were applied.
Mykyta Levchenko, Oleksandr Gryshyn, Oleksandr Velychko, Oleksandr Grek, Anzhela Nadtochiy, Olena Volkova   +5 more
wiley   +1 more source