矿业科学技术学报(英文版)2023,Vol.33Issue(12) :1437-1449.DOI:10.1016/j.ijmst.2023.10.006

Extraction and imaging of indicator elements for non-destructive,in-situ,fast identification of adverse geology in tunnels

Fumin Liu Peng Lin Zhenhao Xu Ruiqi Shao Tao Han
矿业科学技术学报(英文版)2023,Vol.33Issue(12) :1437-1449.DOI:10.1016/j.ijmst.2023.10.006

Extraction and imaging of indicator elements for non-destructive,in-situ,fast identification of adverse geology in tunnels

Fumin Liu 1Peng Lin 2Zhenhao Xu 2Ruiqi Shao 2Tao Han1
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作者信息

  • 1. School of Qilu Transportation,Shandong University,Jinan 250061,China
  • 2. Geotechnical and Structural Engineering Research Center,Shandong University,Jinan 250061,China
  • 折叠

Abstract

The lag in quantitative methods and detection techniques for geologic information has resulted in time-consuming and human-experienced geologic analysis in tunnels.Geochemical indicators of rocks can be used to identify adverse geology and to explain the intrinsic causes of damage to normal rocks.This study proposes a method to identify adverse geology by extracting and imaging the indicator elements.The mapping relationship between rock components and geologic bodies is quickly determined by indicator element extraction based on factor analysis,and then the data are gridded for image output.The location and size of the target adverse geology are visually identified through the distribution images of the indi-cator elements,thus reducing data dimensions and analysis time.A non-destructive,in-situ and fast ele-ment detection technique in tunnels was adopted to speed up the process of geology identification.The accuracy of the detection was validated by comparing field and laboratory test results.This study further confirms and refines the previous research,and the results provide references for geological,mining and underground projects.

Key words

Adverse geology identification/Indicator elements/Rock geochemistry/Tunnel engineering/Geological analysis

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基金项目

National Natural Science Foundation of China(52022053)

National Natural Science Foundation of China(52279103)

Natural Science Foundation of Shandong Province,China(ZR201910270116)

Natural Science Foundation of Shandong Province,China(ZR2023YQ049)

出版年

2023
矿业科学技术学报(英文版)
中国矿业大学

矿业科学技术学报(英文版)

CSTPCDCSCDEI
影响因子:1.222
ISSN:2095-2686
参考文献量3
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