4.7 Article

Study on an improved real-time monitoring and fusion prewarning method for water inrush in tunnels

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tust.2021.103884

Keywords

Water inrush; Sensitive information; Real-time monitoring; Fusion analysis; Early warning

Funding

  1. National Science Foundation for Distinguished Young Scholars of China [52025091]
  2. Joint Funds of the National Natural Science Foundation of China [U1934218]
  3. Shandong Provincial Key Research and Development Program (Major Scientific and Technological Innovation Project) [2019JZZY010601, 2019JZZY010428]
  4. Natural Science Foundation of Chongqing [cstc2019jcyjmsxmX0813]

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The study proposed a new real-time monitoring and fusion prewarning method for tunnel water inrush, which included sensitive information analysis, improved sensor measurement methods, and a new early warning method for multi-information fusion. This method was successfully applied to the Yuelongmen tunnel and proved to be effective and practical in preventing and controlling water inrush during tunnel construction.
As a common geological hazard in tunnel construction, monitoring and early warning is an effective way to prevent and control the occurrence of water inrush. However, the current monitoring and early warning method has areas that require improvement, including a lack of theoretical basis in monitoring information, the inability of real-time monitoring technology during tunnel construction, and the difficulty of fusing massive monitoring data. Therefore, a new real-time monitoring and fusion prewarning method for tunnel water inrush was proposed. First, sensitive information on the evolution process of water inrush was analyzed. Second, an improved method for the accurate measurement of sensors and wireless transmission bands suitable for complex tunnel environments was studied, and a real-time monitoring system for water inrush in tunnels was established. Third, a new early warning method for multi-information interval fusion based on evidence and fuzzy set theory was presented to realize the fusion of massive monitoring data in time series. Furthermore, the proposed method was successfully applied to the crossing river section of the Yuelongmen tunnel. The results had good agreement with the actual excavation situation, which verified that the proposed method was effective and practical.

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