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Research and design of intelligent mine ventilation construction architecture.

Authors :
Huang, Xu
Liu, Yunlong
Source :
International Journal of Low Carbon Technologies. 2022, Vol. 17, p1232-1238. 7p.
Publication Year :
2022

Abstract

The mine ventilation system plays a role in purifying the air and providing a good working environment in coal mine production. Aiming at the unclear concept and inconsistency in solving problems in the process of intelligent construction of mine ventilation system, this paper conducts exploratory research on the connotation of mine ventilation intelligence, theoretical structure model, construction logic and scientific problems to be solved by means of literature review, on-site investigation and qualitative analysis. The research results show that the mine ventilation intelligent system needs to use real-time and full monitoring data, and by integrating brain science principles, machine learning and analysis and other technologies, it can immediately correct the air volume distribution defects, realize automatic power adjustment, remote facility management and control and accurate disaster identification. The theoretical model from the inside to the outside is the concept layer, the key scientific issues and technology layer, the model layer, the application layer and the theoretical support layer. The intelligent process of mine ventilation needs to comprehensively consider the relationship between the conscious human body, the cyber body and the ventilation physical entity in the processes of knowledge accumulation, knowledge modeling, knowledge movement, innovation and optimization, learning progress and feedback evolution. The intelligent ventilation system consists of perception layer, transmission layer and application layer. The research provides a theoretical basis for the intelligent construction of mine ventilation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17481317
Volume :
17
Database :
Academic Search Index
Journal :
International Journal of Low Carbon Technologies
Publication Type :
Academic Journal
Accession number :
161475206
Full Text :
https://doi.org/10.1093/ijlct/ctac104