Development and Application of a Distributed and Parallel Dynamic Grouting Monitoring System Based on an Electrical Resistivity Tomography Method

To address the technical challenges in dynamic monitoring of grout diffusion patterns under complex geological conditions, in this study, a distributed parallel grouting monitoring system based on electrical resistivity tomography was developed. The system achieves three-dimensional visualization of grout propagation through hardware architecture innovation and the integration of inversion algorithms. At the hardware level, a cascadable distributed data acquisition terminal was designed, employing a dynamic optimization strategy for electrode combinations. This breakthrough overcomes traditional serial acquisition limitations. Algorithmically, a Bayesian estimation-based geological unit merging inversion model was proposed; it dynamically calculates merging thresholds through the noise posterior probability, achieving an improvement of more than 30% in the inversion boundary resolution compared with traditional least squares methods. Numerical simulations and physical experiments demonstrated that dipole arrays with 0.5 m electrode spacing exhibit optimal sensitivity to variations in grout resistivity, accurately capturing electrical response characteristics during diffusion. In practical roadbed grouting applications, the system yielded a grout diffusion radius showing only a 0.3 m deviation from the core sampling verification results, with three-dimensional imaging clearly depicting the diffusion morphology. This system provides reliable technical support for the precise control and quality assessment of underground engineering grouting processes.

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Publication Details

Journal
Applied Sciences
Published
2025-09-24
DOI
https://doi.org/10.3390/app151910375
Primary Topic
Geoscience and Mining Technology
Type
article
Field-Weighted Citation Impact
0.00

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Development and Application of a Distributed and Parallel Dynamic Grouting Monitoring System Based on an Electrical Resistivity Tomography Method

Hu Zeng, Qianli Zhang, Cui Du, Jianping Li et al.
Applied Sciences
Geoscience and Mining Technology
article

Development and Application of a Distributed and Parallel Dynamic Grouting Monitoring System Based on an Electrical Resistivity Tomography Method

Hu Zeng, Qianli Zhang, Cui Du, Jianping Li, Jie Liu
article en

Abstract

To address the technical challenges in dynamic monitoring of grout diffusion patterns under complex geological conditions, in this study, a distributed parallel grouting monitoring system based on electrical resistivity tomography was developed. The system achieves three-dimensional visualization of grout propagation through hardware architecture innovation and the integration of inversion algorithms. At the hardware level, a cascadable distributed data acquisition terminal was designed, employing a dynamic optimization strategy for electrode combinations. This breakthrough overcomes traditional serial acquisition limitations. Algorithmically, a Bayesian estimation-based geological unit merging inversion model was proposed; it dynamically calculates merging thresholds through the noise posterior probability, achieving an improvement of more than 30% in the inversion boundary resolution compared with traditional least squares methods. Numerical simulations and physical experiments demonstrated that dipole arrays with 0.5 m electrode spacing exhibit optimal sensitivity to variations in grout resistivity, accurately capturing electrical response characteristics during diffusion. In practical roadbed grouting applications, the system yielded a grout diffusion radius showing only a 0.3 m deviation from the core sampling verification results, with three-dimensional imaging clearly depicting the diffusion morphology. This system provides reliable technical support for the precise control and quality assessment of underground engineering grouting processes.

Applied SciencesVol. 15(19)
China Academy of Railway Sciences (CN)
China Academy of Railway Sciences
Openalex Percentile: Top 68%
Geoscience and Mining Technology
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