Coal Gangue Recognition during Coal Preparation Using an Adaptive Boosting Algorithm
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. This paper proposed a coal gangue image recognition algorithm and a strong classifier based on the AdaBoost algorithm with a genetic algorithm (GA ...
Guanghui Xue, Sicong Han
exaly +3 more sources
Vibration Test of Single Coal Gangue Particle Directly Impacting the Metal Plate and the Study of Coal Gangue Recognition Based on Vibration Signal and Stacking Integration [PDF]
In order to realize the recognition of coal gangue in the top coal caving process, a scheme of the coal gangue recognition based on the collision vibration signal between coal gangue and the metal plate is proposed in this paper, a systematic and ...
Yang Yang +3 more
doaj +4 more sources
Research on coal gangue recognition algorithm based on HGTC-YOLOv8n model
The existing deep learning based coal gangue recognition methods have problems in complex working conditions such as low lighting, high noise, and motion blur in coal mines, such as low precision of coal gangue recognition, easy omission of small target ...
TENG Wenxiang, WANG Cheng, FEI Shuhui
doaj +3 more sources
Research on coal gangue recognition method based on infrared thermal imaging
Coal and gangue sorting methods based on heavy-medium coal selection technology, jigging technology, flotation technology, dry coal selection technology and γ-ray detection method have high investment costs, low sorting efficiency and serious ...
CHENG Gang +3 more
doaj +3 more sources
Coal gangue recognition of top coal caving is one of the important links in the process of intelligent coal mine construction. However, the recognition accuracy of this technology in practical application is still challenging, because the recognition ...
He Li +3 more
doaj +2 more sources
Multi-Strategy Improvement of Coal Gangue Recognition Method of YOLOv11. [PDF]
The current methods for detecting coal gangue face several challenges, including low detection accuracy, a high probability of missed detections, and inadequate real-time performance. These issues stem from the complexities associated with diverse industrial environments and mining conditions, such as the mixing of coal gangue and insufficient ...
Tao H, Zhang L, Sun Z, Cui X, Yi W.
europepmc +4 more sources
Research progress and key technologies of intelligent coal-gangue sorting robot
The gangue is wrapped by slurry in underground coal mine, which causes difficult coal-gangue recognition and sorting. The underground working space is narrow, so the equipment layout is difficult, and the diversion of coal-gangue is difficult. Therefore,
ZHANG Ye +5 more
doaj +2 more sources
YOLOv4-Tiny-Based Coal Gangue Image Recognition and FPGA Implementation
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, huge size, and significant heat generation.
Shanyong Xu +3 more
openaire +4 more sources
Research on efficient matching method of coal gangue recognition image and sorting image. [PDF]
Abstract The coal gangue sorting robot may encounter variations in the pose of the target coal gangue due to belt slippage, deviation, and speed fluctuations, leading to failed or missed grasping attempts during the sorting process of coal gangue.
Ye Z +5 more
europepmc +4 more sources
Experimental platform for coal gangue sorting robot based on image detection
Currently, coal gangue pre-sorting is still mostly done manually, with high labor intensity, low sorting efficiency, and safety hazards. Using coal gangue sorting robots to replace manual coal gangue pre-sorting is an effective way to ensure the health ...
LI Sanxi +4 more
doaj +2 more sources

