Research Progress on Intelligent Perception Technology for Wind Speed in Mine Tunnels

CHEN Xuanzhong; WANG Xiaodong; YANG Yijie; LYU Yuqi; LIU Chang; DU Qingwen; XIE Bo

doi:10.13779/j.cnki.issn1001-0076.2024.04.014

Conservation and Utilization of Mineral Resources > 2024 > 44(4): 124-134. > DOI: 10.13779/j.cnki.issn1001-0076.2024.04.014

CHEN Xuanzhong，WANG Xiaodong，YANG Yijie，LYU Yuqi，LIU Chang，DU Qingwen，XIE Bo．Research progress on intelligent perception technology for wind speed in mine tunnels[J]. Conservation and Utilization of Mineral Resources，2024，44（4）：124−134. DOI: 10.13779/j.cnki.issn1001-0076.2024.04.014

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Research Progress on Intelligent Perception Technology for Wind Speed in Mine Tunnels

1.
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, Yunnan, China
2.
Kunming University of Science and Technology, Faculty of Public Security and Emergency Management, Kunming 650093, Yunnan, China

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Received Date: June 12, 2024
Issue Publish Date: August 29, 2024

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Abstract

Abstract

The intelligent mine ventilation systems is a key link of advancing intelligent mine construction and ensuring safe mine production. As the fundamental data source, ventilation parameters are essential for the intelligent construction of mine ventilation systems. However, during the development of intelligent wind speed sensing technology for mine tunnels, there are key scientific and technological issues that need to be addressed, such as optimizing sensor accuracy and reliability, correcting sensor wind measurement errors, intelligent and rapid prediction of average wind speed, and optimizing sensor layout. This paper studies the cutting−edge achievements in the field from aspects such as sensor technology and high−precision intelligent wind speed prediction, summarizes the advantages, disadvantages, and applicable scopes of various technologies, and proposes an intelligent prediction model for the average wind speed in tunnel sections based on the PSO−GRU neural network. This model can effectively improve the accuracy of calculating the average wind speed in mine tunnels and provide a theoretical reference for the development of intelligent sensing technology for ventilation parameters.
- mine ventilation,
- tunnel airflow characteristics,
- wind speed sensor,
- average wind speed in tunnels,
- PSO−GRU neural network

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References (59)

References

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