Gong-kuang zidonghua (Sep 2023)

Advancements and applications: In-situ monitoring technology for overburden movement in mining

  • ZHU Weibing,
  • WANG Xiaozhen,
  • XIE Jianlin,
  • ZHAO Bozhi,
  • NING Shan,
  • XU Jialin

DOI
https://doi.org/10.13272/j.issn.1671-251x.18136
Journal volume & issue
Vol. 49, no. 9
pp. 1 – 12

Abstract

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The in-situ monitoring technology for overburden movement in mining has the features of adapting to complex geological conditions in deep shaft high pressure water and thick coal seam mining, multi layer dynamic monitoring, and high-precision remote real-time online transmission. It provides effective data support for mining enterprises to carry out roof disaster prevention and control. Starting from the practical background of coal mining application, this paper systematically reviews the development process, technological progress, and application effects of in-situ monitoring technology for overburden movement in mining. Based on the development history of mining pressure theory and overburden movement monitoring technology in China, this paper comprehensively introduces the important stages of in-situ monitoring technology for overburden movement in mining. It elaborates on the theoretical innovation and technological breakthroughs achieved by this technology in three aspects: multidimensional real-time collaborative monitoring, unmanned online monitoring, and deep rock movement monitoring. Based on the monitoring engineering examples of coal mines such as Bulianta Coal Mine, Tongxin Coal Mine, and Gaojiabao Coal Mine, the effectiveness of in-situ monitoring technology for overburden movement in mining is demonstrated in practical engineering applications. The application prospects of this technology in different types of mining areas and research fields are discussed. It is pointed out that the development trend of in-situ monitoring technology for overburden movement in mining is precision, intelligence, and integration, namely optimizing sensor performance and layout plans to improve monitoring precision and accuracy, using artificial intelligence, big data, and Internet of things technology to achieve automatic analysis and prediction, combining the in-situ monitoring technology with other technologies to form a complete monitoring system.

Keywords