Results 121 to 130 of about 381 (161)
Coal Gangue Recognition during Coal Preparation Using an Adaptive Boosting Algorithm
Minerals (Basel, Switzerland), 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. 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
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Powder Technology, 2021
Abstract Advancing of the intelligent fully mechanized caving mining technology (IFMCMT) is the fundamental method to improve the output of coal resources. Accurate identification of coal gangue is the necessary condition for the realization of IFMCMT.
Yang Yang
exaly +2 more sources
Abstract Advancing of the intelligent fully mechanized caving mining technology (IFMCMT) is the fundamental method to improve the output of coal resources. Accurate identification of coal gangue is the necessary condition for the realization of IFMCMT.
Yang Yang
exaly +2 more sources
Recognition of Coal and Gangue Based on X-Ray
Applied Mechanics and Materials, 2013In this paper,a recognition method of coal and gangue based on x-ray is studied. With the different density , the coal and gangue on a belt can be detected by x-ray. After penetrated by x-ray, with the acquisition of ray signal and image analysis, the gangue can be accurately distinguished from the coal.
Yi Ding Zhao, Xiaoming He
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Research on coal gangue recognition method based on XBS-YOLOv5s
Measurement Science and Technology, 2023Abstract Aiming at the problems of misdetection, omission and low recognition accuracy of coal gangue recognition due to the harsh environmental factors such as low illumination, motion blur and large quantities of coal gangue mixing in coal mines, a coal gangue recognition method based on XBS-YOLOv5s is proposed.
Yuhao Yang +6 more
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Research on recognition of coal and gangue based on image processing
World Journal of Engineering, 2015In order to avoid the waste of water resources and environmental pollution caused by separating coal and gangue in the traditional methods, a novel method based on image processing is proposed in this paper. Firstly the image of coal or gangue is preprocessed.
Lihong Li, Haijiang Wang, Lei An
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Coal Gangue Interface Recognition Based on MFCC Research
Applied Mechanics and Materials, 2013In view of the existing coal gangue interface identification technology use ray method that it is not applicable to the working face what it dose not contain radioactive elements in the roof or contain low amounts of radioactive elements, and the detection range of radar detection is lesser, the signal attenuation is relatively serious, so putting ...
Ai Xiang He +2 more
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An Image Recognition Approach for Coal and Gangue Used in Pick-Up Robot
2018 IEEE International Conference on Real-time Computing and Robotics (RCAR), 2018Picking gangue from raw coal is a crucial step of coal production. Due to the potential for replacing manual workers, the study of pick-up robot is attracting much interest. Pick-up robots usually work in fixed working areas where the types of coals and gangues are unitary.
Man Li, Kaikai Sun
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Coal-Gangue Acoustic Signal Recognition Based on Sparse Representation
Applied Mechanics and Materials, 2013Our country has rich coal resources. Further research is great significant to realize the automation of top coal caving mining technology. This paper presents a new method based on sparse representation for coal and gangue signal recognition. To solve the mining noise problem, the wavelet analysis is used to filter and de-noising. Sparse representation
Ai Xiang He, Nan Liu, Guang Fei Wei
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A fast recognition method for coal gangue image processing
Multimedia Systems, 2023Dailiang Wei +6 more
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Research on Recognition Algorithm Based on Polarization Characteristics of Coal and Gangue Surface
Proceedings of the 15th International Conference on Digital Image Processing, 2023Zhiying Tan +3 more
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