Three-Dimensional ERT Advanced Detection Method with Source-Position Electrode Excitation for Tunnel-Boring Machines

Area of Science:

• Geophysics
• Civil Engineering
• Electrical Resistivity Tomography (ERT)

Background:

• Tunnel-boring machines (TBMs) are essential for urban underground construction but face geological hazards like faults and water surges.
• Existing geophysical methods have limitations in the confined space of shield tunnels, hindering real-time hazard detection.
• Accurate, real-time detection of geological conditions ahead of the TBM is crucial for preventing damage and ensuring safety.

Purpose of the Study:

• To propose and validate an advanced 3D Electrical Resistivity Tomography (ERT) detection method for shield tunnel construction.
• To address the limitations of current geophysical methods in detecting geological anomalies in front of TBMs.
• To enable continuous, real-time monitoring of subsurface conditions during TBM tunneling.

Main Methods:

• Designed a source-position electrode array integrated into the TBM cutterhead for data acquisition in the shield tunnel environment.
• Developed a 3D finite element tunnel model with high- and low-resistance anomalies to simulate geological conditions.
• Employed the GREIT reconstruction algorithm for 3D imaging of anomalous bodies ahead of the tunnel face.
• Conducted physical simulation experiments using a laboratory platform to verify the method's effectiveness.

Main Results:

• The 3D-ERT method successfully reconstructed the position and shape of anomalous bodies in front of the tunnel face.
• Laboratory experiments validated the capability of the proposed method to detect subsurface anomalies.
• The integrated electrode array provided secure data for inverse imaging.

Conclusions:

• The developed 3D-ERT method offers a novel and effective solution for real-time geological condition detection in shield tunneling.
• This approach enhances safety and efficiency in TBM operations by providing crucial information about upcoming geological challenges.
• The study provides a new strategy for continuous subsurface monitoring during the tunnel boring process.