›› 2018, Vol. 39 ›› Issue (7): 2509-2517.doi: 10.16285/j.rsm.2018.0117

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Identification method of water inrush status based on multiple monitoring information fusion analysis

CHENG Shuai, LI Shu-cai, LI Li-ping, SHI Shao-shuai, ZHOU Zong-qing, YUAN Yong-cai   

  1. Geotechnical and Structural Engineering Research Center, Shandong University, Jinan, Shandong 250061, China
  • Received:2018-01-19 Online:2018-07-10 Published:2018-08-05
  • Supported by:

    This work was supported by the National Key Research and Development Program of China (2016YFC0801607, 2016YFC0801604), the National Natural Science Foundation of China (51679131, 51709159) and the Fundamental Research Funds of Shandong University (2015GN029, 2016GN026).

Abstract: The process of water inrush disaster accompanied by the information change of rock and soil within the preventing structure changed accordingly. This study conducted an in-depth fusion analysis of multi-physical field information for potential water inrush channels. The logical symbiosis relationship of multi-information was revealed, and a theoretical method for identifying the evolution state of water inrush was established. Two typical similarity model tests of water inrush were conducted to simulate the progressive failure of rock mass and filling structure instability. Then, we proposed the correlation between the multiple monitoring information and the quantitative characterisation function. Based on the theory of principal component analysis, this study revealed the logical symbiosis relationship between multiple parameters and determined the influence weight of the multi-physical field information in the surrounding rock, which provided a theoretical basis for the monitoring design and early warning of water inrush disaster. A comprehensive method for the evolution state of water inrush disaster was established, combined with the extreme point and the stagnation point of the fitting curve representing the changing trend of the function, Finally, the evolution stages of these two types of water inrush are divided into four periods: calming period, development period, abrupt period and post-disaster period. The energy discrimination method of the occurrence probability of water inrush was put forward at any moment. The theoretical method provides a reference for monitoring and early warning of water inrush disaster in tunnels and underground engineering.

Key words: water inrush, multiple information, status identification, principal component analysis

CLC Number: 

  • U 45

[1] LI Li-ping, ZHU Yu-ze, ZHOU Zong-qing, SHI Shao-shuai, CHEN Yu-xue, TU Wen-feng, . Calculation methods of rock thickness for preventing water inrush in tunnels and their applicability evaluation [J]. Rock and Soil Mechanics, 2020, 41(S1): 41-50.
[2] LI Xiao-fei, SUN Jiang-tao, CHEN Wei-zhong, YUAN Jing-qiang, LIU Jin-quan, ZHANG Qing-yan,. Strength and anti-washout property of fiber silica fume cement grout [J]. , 2018, 39(9): 3157-3163.
[3] LI Chun-yuan, ZHANG Yong, PENG Shuai, GAO Shou-yang, MA Ya-zhong,. Strong disturbance hazard analysis of unloading damage for floor rock mass in deep coal mining [J]. , 2018, 39(11): 3957-3968.
[4] SUN Yun-jiang, ZUO Jian-ping, LI Yu-bao, LIU Cun-hui, LI Yan-hong, SHI Yue,. Micro-seismic monitoring on fractured zone and water inrush mechanism analysis of deep mining above aquifer in Xingdong coalmine [J]. , 2017, 38(8): 2335-2342.
[5] LIU Jin-quan, YANG Dian-sen, CHEN Wei-zhong, YUAN Jing-qiang,. Research on particle starting velocity in the expansion of water inrush channel in completely weathered granite [J]. , 2017, 38(4): 1179-1187.
[6] YANG Zi-han, YANG Xiao-li, XU Jing-shu, LI Yong-xin, SUN Zhi-bin,. Two methods for rock wall thickness calculation in karst tunnels based on upper bound theorem [J]. , 2017, 38(3): 801-809.
[7] HUANG Dan, LI Xiao-qing. Numerical simulation research on characteristic strength of marble based on development of microcrack [J]. , 2017, 38(1): 253-262.
[8] QIAN Zhao-ming, REN Gao-feng, CHU Fu-jiao, QIN Shao-bing, . Rock mass quality classification based on PCA and Fisher discrimination analysis [J]. , 2016, 37(S2): 427-432.
[9] GONG Feng-qiang , LI Jia-wei,. Discrimination model of sandy soil liquefaction based on PCA-DDA principle and its application [J]. , 2016, 37(S1): 448-454.
[10] ZHANG Shi-chuan , GUO Wei-jia , SUN Wen-bin , LI Yang-yang , WANG Hai-long , . Experimental research on extended activation and water inrush of concealed structure in deep mining [J]. , 2015, 36(11): 3111-3120.
[11] YU Wen-sheng , LI Peng , ZHANG Xiao , WANG Qian,. Model test research on hydrodynamic grouting for single fracture with variable inclinations [J]. , 2014, 35(8): 2137-2143.
[12] ZHOU Zong-qing ,LI Shu-cai ,LI Li-ping ,SHI Shao-shuai ,SONG Shu-guang ,WANG Kai . Attribute recognition model of fatalness assessment of water inrush in karst tunnels and its application [J]. , 2013, 34(3): 818-826.
[13] LI Shu-cai , ZHAO Yan , XU Bang-shu , LI Li-ping , LIU Qin , WANG Yu-kui . Study of determining permeability coefficient in water inrush numerical calculation of subsea tunnel [J]. , 2012, 33(5): 1497-1504.
[14] XU Bin , ZHANG Yan , JIANG Ling . Coupled model based on grey relational analysis and stepwise discriminant analysis for water source identification of mine water inrush [J]. , 2012, 33(10): 3122-3138.
[15] SHI Yong-qiang , ZHAO Jian-bin , YANG Jun. Optimized neural network model for predicting ultimate bearing capacity of statically-pressured pipe pile based on principal component analysis [J]. , 2011, 32(S2): 634-640.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!