Evidence map›Paper›PMID 41597911›Full record

ArticleMicromachines2026

Research on a Self-Powered Vibration Sensor for Coal Mine In Situ Stress Fracturing Drilling.

Jiangbin Liu, Mingzhong Li, Chuan Wu, Xianhong Shen, Yanjun Feng

Abstract read
In one paragraph

Article in Micromachines, 2026. 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

5 authors.

Jiangbin LiuCoal Mining Branch, China Coal Research Institute, Beijing 100013, China.
Mingzhong LiBeijing Tianma Intelligent Control Technology Co., Ltd., Beijing 100399, China.
Chuan WuFaculty of Mechanical and Electronic Information, China University of Geosciences (Wuhan), Wuhan 430074, China.ORCID 0000-0002-7275-0295
Xianhong ShenFaculty of Mechanical and Electronic Information, China University of Geosciences (Wuhan), Wuhan 430074, China.
Yanjun FengChina Coal Technology & Engineering Group Coal Mining Research Institute, Beijing 100013, China.

Funding

National Key Research and Development Program of China 2024YFC2814304
6 · The paper itself

Abstract

In the process of in situ stress fracturing drilling in coal mines, obtaining downhole vibration data not only improves drilling efficiency but also plays a key role in ensuring operational safety. Nevertheless, the energy supply techniques used in current vibration detectors reduce operational performance and escalate excavation expenses. This research proposes a self-powered vibration sensor based on the triboelectric nanogenerator, designed for the operational environment of coal mine in situ stress fracturing drilling. It can simultaneously detect axial and lateral vibration frequencies, and the inclusion of redundant sensing units provides the sensor with high reliability. Experimental outcomes demonstrate that the device functions across a frequency span of 0 to 11 Hz, maintaining error margins for frequency and amplitude under 4%. Furthermore, it functions reliably in environments where temperatures are under 150 °C and humidity is under 90%, proving its strong resilience to environmental factors. In addition, the device possesses self-generating potential, achieving a maximum voltage of 68 V alongside an output current of 51 nA. When connected to a 6 × 10

Indexed as

high reliabilityself-poweredtriboelectric nanogeneratorvibration sensors

Identifiers

PMID41597911
PMCPMC12843646

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.