Evidence map›Paper›PMID 36236692›Full record

ArticleSensors (Basel, Switzerland)2022

A Novel High-Sensitivity MEMS Pressure Sensor for Rock Mass Stress Sensing.

Honghui Wang, Dingkang Zou, Peng Peng, Guangle Yao, Jizhou Ren

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Reciprocating Arc Silicon Strain Gauges.Sensors (Basel, Switzerland) · 2023
    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

5 authors.

Honghui WangState Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.ORCID 0000-0001-9257-2820
Dingkang ZouState Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China.
Peng PengCollege of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu 610059, China.
Guangle YaoCollege of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu 610059, China.
Jizhou RenCollege of Computer Science and Cyber Security, Chengdu University of Technology, Chengdu 610059, China.

Funding

National Key Research and Development Program of China 2019YFC1509602Sichuan Science and Technology Program 2021YFG0377Sichuan Science and Technology Program 2021YFS0324State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project SKLGP2019Z012
6 · The paper itself

Abstract

This paper proposes a novel high-sensitivity micro-electromechanical system (MEMS) piezoresistive pressure sensor that can be used for rock mass stress monitoring. The entire sensor consists of a cross, dual-cavity, and all-silicon bulk-type (CCSB) structure. Firstly, the theoretical analysis is carried out, and the relationship between the structural parameters of the sensor and the stress is analyzed by finite element simulation and curve-fitting prediction, and then the optimal structural parameters are also analyzed. The simulation results indicate that the sensor with the CCSB structure proposed in this article obtained a high sensitivity of 87.74 μV/V/MPA and a low nonlinearity error of 0.28% full-scale span (FSS) within the pressure range of 0-200 MPa. Compared with All-Si Bulk, grooved All-Si Bulk, Si-Glass Bulk, silicon diaphragm, resistance strain gauge, and Fiber Bragg grating structure pressure sensors, the designed sensor has a significant improvement in sensitivity and nonlinearity error. It can be used as a new sensor for rock disaster (such as collapse) monitoring and forecasting.

Indexed as

MEMSpiezoresistive pressure sensorrock stress sensingsimulation

Identifiers

PMID36236692
PMCPMC9570841

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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.