Results 31 to 40 of about 4,764 (197)

Research on method of acquiring high quality coal gangue images under multi-factor illumination condition

open access: yesMeitan kexue jishu, 2023
Aiming at the problem of poor imaging quality of coal and gangue surface features and low identification rate of coal and gangue caused by insufficient illumination conditions in the process of online coal separation,a new high-quality coal gangue image ...
CAO Xiangang   +5 more
doaj   +1 more source

Image feature extraction and recognition model construction of coal and gangue based on image processing technology

open access: yesScientific Reports, 2022
Using image recognition technology to realize coal gangue recognition is one of the development directions of intelligent fully mechanized caving mining.
Lei Zhang   +4 more
doaj   +1 more source

Coal and gangue identification method based on EMD feature extraction and random forest

open access: yesGong-kuang zidonghua, 2021
Identification based on vibration signals is an effective method to realize coal and gangue identification in fully mechanized mining. The existing method needs to be further studied in terms of identification accuracy and effectiveness.
DOU Xijie   +5 more
doaj   +1 more source

Design of automatic identification system of coal and gangue for fully-mechanized coal caving working face and its applicatio

open access: yesGong-kuang zidonghua, 2014
An automatic identification system of coal and gangue for fullly-mechanized coal caving working face based on vibration signal was proposed, structure and working principle of the system were introduced and design schemes of software and hardware of coal
ZHANG Liang   +3 more
doaj   +1 more source

Research on multi-manipulator coal and gangue sorting robot system based on machine visio

open access: yesGong-kuang zidonghua, 2019
Existing coal and gangue sorting methods mainly use image processing and pattern recognition technology to identify and sort coal and gangue according to texture characteristic values of coal and rock.
WANG Peng   +4 more
doaj   +1 more source

A Study of Multispectral Technology and Two-Dimension Autoencoder for Coal and Gangue Recognition

open access: yesIEEE Access, 2020
Coal is one of the main sources of human energy. In the process of coal mining, separating gangue from coal has great significance for environmental protection and energy conservation.
Wenhao Lai   +4 more
doaj   +1 more source

Gangue Source Reduction Technology and Process Optimization Based on Underground Coal Gangue Photoelectric Separation

open access: yes, 2023
The precise identification of damp, sticky coal gangue; efficient jet nozzle separation; and process layout in a narrow, restricted space are essential technologies for gangue source reduction based on underground gangue photoelectric separation, which ...
Liansheng Li   +6 more
core   +1 more source

Coal Gangue Recognition during Coal Preparation Using an Adaptive Boosting Algorithm

open access: yes, 2023
The recognition of coal and gangue is the premise and foundation of coal gangue intelligent sorting. Adaptive boosting (AdaBoost) algorithm-based coal gangue identification has not been studied in depth.
Sanxi Li   +5 more
core   +1 more source

Research and application of key technology of intelligent coal caving in high gas fully-mechanized top coal caving face [PDF]

open access: yes, 2023
At present, intelligent coal caving in high gas fully mechanized top coal caving face is facing many problems, mainly including poor recognition accuracy of coal gangue, incomplete control research on coal flow and gas concentration, cumbersome design ...
Yao CUI   +3 more
core   +1 more source

YOLOv4-Tiny-Based Coal Gangue Image Recognition and FPGA Implementation

open access: yes, 2022
Nowadays, most of the deep learning coal gangue identification methods need to be performed on high-performance CPU or GPU hardware devices, which are inconvenient to use in complex underground coal mine environments due to their high power consumption ...
Yourui Huang   +7 more
core   +1 more source

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