中国铁路2024,Issue(1) :67-74.DOI:10.19549/j.issn.1001-683x.2023.04.12.002

敞开式小直径TBM隧洞综合超前地质预报技术研究与应用

Research and Application of Comprehensive Advance Geological Prediction Technology for Open Small-diameter TBM Tunnel

黄斌 章龙管
中国铁路2024,Issue(1) :67-74.DOI:10.19549/j.issn.1001-683x.2023.04.12.002

敞开式小直径TBM隧洞综合超前地质预报技术研究与应用

Research and Application of Comprehensive Advance Geological Prediction Technology for Open Small-diameter TBM Tunnel

黄斌 1章龙管1
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作者信息

  • 1. 中铁工程服务有限公司,四川成都 610036
  • 折叠

摘要

TBM在掘进过程中面临复杂地质、超小直径、超小转弯半径以及坡度大、隧洞长等诸多技术难题,卡机和突水突泥时有发生.为解决TBM在小半径隧洞施工中所面临的重大风险,提出基于TBM隧洞的双震源系统与激电二极三维相结合的综合超前地质预报技术;以安徽桐城抽水蓄能电站自流排水洞TBM项目为例,实现预报设备与小直径TBM相搭载;通过智能图谱识别及全空间多场信息融合与深度学习反演成像,实时预报掘进过程中掌子面前方地质状况.该应用切实解决了小直径TBM隧洞超前地质探测难题,可为同类工程TBM高效掘进提供参考.

Abstract

Tunneling using a TBM encounters many technical challenges during its process,including complex geology,very small diameter,very small turning radius,steep gradient,and long tunnel,causing frequent machine jamming and water and mud gushing.To mitigate major risks in small-radius TBM tunnel construction,a comprehensive advanced geological prediction technology is proposed.This technology combines a dual-source system and an IP dipole 3D system for TBM tunnels.To exemplify this approach,the gravity drainage tunnel project at the Tongcheng Pumped Storage Power Station in Anhui Province serves as an example.Prediction equipment was installed on the TBM with a small diameter,allowing the real-time prediction of geological conditions ahead of the working face.This was achieved through intelligent graph identification,full-space multi-field information fusion,deep learning,and inversion imaging.The application effectively addresses the advanced geological investigation challenges encountered in small-diameter TBM tunnels,providing a reference for efficient TBM tunneling of similar projects.

关键词

开敞式小直径/TBM/地震波法/电法/隧洞综合超前地质预报

Key words

open small-diameter/TBM/seismic wave method/electrical method/comprehensive advance geological prediction of tunnel

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基金项目

中国中铁重大专项科技开发项目(2021-专项-05)

中铁工程服务有限公司科技开发项目(KY2019102401)

出版年

2024
中国铁路
中国铁道科学研究院

中国铁路

CSTPCD北大核心
影响因子:0.407
ISSN:1001-683X
参考文献量12
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