Results 161 to 170 of about 1,612 (205)

Measurement of sulfur content in coal mining areas by using field-remote sensing data and an integrated deep learning model. [PDF]

PeerJ Comput Sci
Liu J, Le BT.
europepmc   +1 more source

Optimization study on transverse mining zoning during the capacity expansion stage of nearly horizontal open-pit coal mines. [PDF]

Sci Rep
Wen Y, Song Z, Su Q, Liu Z, Wu C, Zhang L.   +5 more
europepmc   +1 more source

Development of a deep learning-based foreign object detection algorithm for coal mine conveyor belts. [PDF]

Sci Rep
Ling J, Fu Z, Yuan X, Ling R.
europepmc   +1 more source

Prediction of Temperature Intervals Driven by Multiple Indicator Gases during Spontaneous Coal Combustion and Oxidation. [PDF]

ACS Omega
Zhang T, Jia B, Zhang D, Jia J.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Research on coal gangue recognition method based on XBS-YOLOv5s

Measurement Science and Technology, 2023
Abstract 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, Deyong Li, Yongcun Guo, Shuang Wang, Dongyang Zhao, Wei Chen, Hui Zhang   +6 more
openaire   +1 more source

Impact-slip experiments and systematic study of coal gangue “category” recognition technology Part I: Impact-slip experiments between coal gangue mixture and top coal caving hydraulic support and the study of coal gangue “category” recognition technology

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, Qingliang Zeng
openaire   +1 more source

Coal Gangue Interface Recognition Based on MFCC Research

Applied Mechanics and Materials, 2013
In 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, Meng Ke Zhang, Chen Chen Wang   +2 more
openaire   +1 more source

Coal-Gangue Acoustic Signal Recognition Based on Sparse Representation

Applied Mechanics and Materials, 2013
Our 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
openaire   +1 more source

Coal Gangue Recognition Algorithm Based on Improved YOLOv5

2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA), 2021
Fangjun Gui, Shuo Yu, Hailan Zhang, Hongda Zhu   +3 more
openaire   +1 more source