Evidence map›Paper›PMID 31470534›Full record

ArticleSensors (Basel, Switzerland)2019

A Semi-Automatic Coupling Geophone for Tunnel Seismic Detection.

Yao Wang, Nengyi Fu, Zhihong Fu, Xinglin Lu, Xian Liao, Haowen Wang, Shanqiang Qin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Yao WangState Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, No. 174 Shazhengjie, Chongqing 400044, China.
Nengyi FuDepartment of Geophysics, Colorado School of Mines, Golden, CO 80401, USA.
Zhihong FuState Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, No. 174 Shazhengjie, Chongqing 400044, China. fuzhihong@cqu.edu.cn.
Xinglin LuState Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, No. 174 Shazhengjie, Chongqing 400044, China.
Xian LiaoChongqing Triloop Detection Co., Chongqing 402660, China.
Haowen WangSchool of Robot Engineering, Yangtze Normal University, Chongqing 408100, China.
Shanqiang QinSchool of Robot Engineering, Yangtze Normal University, Chongqing 408100, China.ORCID 0000-0001-8398-4874

Funding

the National Key R&D Program of China 2017YFC0601804
6 · The paper itself

Abstract

The tunnel seismic method allows for the detection of the geology in front of a tunnel face for the safety of tunnel construction. Conventional geophones have problems such as a narrow spectral width, low sensitivity, and poor coupling with the tunnel wall. To tackle issues above, we propose a semi-automatic coupling geophone equipped with a piezoelectric sensor with a spectral range of 10-5000 Hz and a sensitivity of 2.8 V/g. After the geophone was manually pushed into the borehole, it automatically coupled with the tunnel wall under the pressure of the springs within the device. A comparative experiment showed that the data spectrum acquired by the semi-automatic coupling geophone was much higher than that of the conventional geophone equipped with the same piezoelectric sensor. The seismic data were processed in combination with forward modeling. The imaging results also show that the data acquired by the semi-automatic coupling geophone were more in line with the actual geological conditions. In addition, the semi-automatic coupling geophone's installation requires a lower amount of time and cost. In summary, the semi-automatic coupling geophone is able to efficiently acquire seismic data with high fidelity, which can provide a reference for tunnel construction safety.

Indexed as

forward modelinggeophonepiezoelectric sensorsemi-automatic couplingtunnel seismic detection

Identifiers

PMID31470534
PMCPMC6749232

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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.