Evidence map›Paper›PMID 38794066›Full record

ArticleSensors (Basel, Switzerland)2024

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

Shuanfeng Zhao, Bo Liu, Bowen Ren, Li Wang, Zhijian Luo, Jian Yao, Yunrui Bai

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shuanfeng ZhaoCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.ORCID 0000-0002-3027-223X
Bo LiuCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Bowen RenCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Li WangCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Zhijian LuoCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Jian YaoCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.
Yunrui BaiCollege of Mechanical Engineering, Xi'an University of Science and Technology, Xi'an 710054, China.

Funding

Qin Chuan yuan "Scientist + Engineer" team construction project No. 2023KXJ-249Shaanxi Provincial Key Research and Development Program Project No.2020ZDLGY04-06
6 · The paper itself

Abstract

Tunnel-boring machines (TBMs) are widely used in urban underground tunnel construction due to their fast and efficient features. However, shield-tunnel construction faces increasingly complex geological environments and may encounter geological hazards such as faults, fracture zones, water surges, and collapses, which can cause significant property damage and casualties. Existing geophysical methods are subject to many limitations in the shield-tunnel environment, where the detection space is extremely small, and a variety of advanced detection methods are unable to meet the required detection requirements. Therefore, it is crucial to accurately detect the geological conditions in front of the tunnel face in real time during the tunnel boring process of TBM tunnels. In this paper, a 3D-ERT advanced detection method using source-position electrode excitation is proposed. First, a source-position electrode array integrated into the TBM cutterhead is designed for the shield-tunnel construction environment, which provides data security for the inverse imaging of the anomalous bodies. Secondly, a 3D finite element tunnel model containing high- and low-resistance anomalous bodies is established, and the GREIT reconstruction algorithm is utilized to reconstruct 3D images of the anomalous body in front of the tunnel face. Finally, a physical simulation experiment platform is built, and the effectiveness of the method is verified by laboratory physical modeling experiments with two different anomalous bodies. The results show that the position and shape of the anomalous body in front of the tunnel face can be well reconstructed, and the method provides a new idea for the continuous detection of shield construction tunnels with boring.

Indexed as

3D-ERTadvanced detectioncutterhead source electrodephysics simulation experimentshield tunnel

Identifiers

PMID38794066
PMCPMC11125436

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.