Evidence map›Paper›PMID 34577757›Full record

ArticleMicromachines2021

Real-Time Built-In Self-Test of MEMS Gyroscope Based on Quadrature Error Signal.

Rui Feng, Jiong Wang, Wei Qiao, Fu Wang, Ming Zhou, Xinglian Shang, Lei Yu, Liuhui Zhou, Shuwen Guo

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

9 authors.

Rui FengEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Jiong WangSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Wei QiaoEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Fu WangEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Ming ZhouEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Xinglian ShangEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Lei YuEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Liuhui ZhouEast China Institute of Photo-Electron IC, Suzhou 215163, China.
Shuwen GuoSchool of Electronic and Information Engineering, Soochow University, Suzhou 251000, China.

Funding

Jiangsu Postdoctoral Research Foundation 1701175C
6 · The paper itself

Abstract

In high-reliability applications, the health condition of the MEMS gyroscope needs to be known in real time to ensure that the system does not fail due to the wrong output signal. Because the MEMS gyroscope self-test based on the principle of electrostatic force cannot be performed during the working state. We propose that by monitoring the quadrature error signal of the MEMS gyroscope in real time, an online self-test of the MEMS gyroscope can be realized. The correlation between the gyroscope's quadrature error amplitude signal and the gyroscope scale factor and bias was theoretically analyzed. Based on the sixteen-sided cobweb-like MEMS gyroscope, the real-time built-in self-test (BIST) method of the MEMS gyroscope based on the quadrature error signal was verified. By artificially setting the control signal of the gyroscope to zero, we imitated several scenarios where the gyroscope malfunctioned. Moreover, a mechanical impact table was used to impact the gyroscope. After a 6000 g shock, the gyroscope scale factor, bias, and quadrature error amplitude changed by -1.02%, -5.76%, and -3.74%, respectively, compared to before the impact. The gyroscope failed after a 10,000 g impact, and the quadrature error amplitude changed -99.82% compared to before the impact. The experimental results show that, when the amplitude of the quadrature error signal seriously deviates from the original value, it can be determined that the gyroscope output signal is invalid.

Indexed as

built-in self-test (BIST)MEMS gyroscopequadrature error

Identifiers

PMID34577757
PMCPMC8469003

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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.