Evidence map›Paper›PMID 42356747›Full record

ArticleSensors (Basel, Switzerland)2026

Reliability Assessment of MEMS Gyroscopes via Dual-Mechanism Synergistic Degradation: A Generalized Linear Model with Physics-Informed Wiener Processes.

Pengbin Yang, Zhen Liu, Yuhang Liang, Xinfeng Guo, Hang Geng

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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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.

Pengbin YangSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0009-0004-1886-500X
Zhen LiuSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0003-3406-0039
Yuhang LiangSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Xinfeng GuoSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Hang GengSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

Funding

National Natural Science Foundation of China U2330206
6 · The paper itself

Abstract

As the core sensor of inertial measurement units, the reliability of Micro-Electro-Mechanical Systems (MEMS) gyroscopes is critical for long-term navigation and motion control applications. To bridge the mechanism-data gap in MEMS multi-mechanism degradation modeling, this paper proposes a physics-informed dual-indicator reliability assessment framework based on Wiener processes. Two degradation indicators under consideration are frequency-related degradation caused by stiffness degradation and Q-factor degradation caused by damping degradation, for which corresponding physics-embedded stochastic degradation models are formulated. The two indicators are normalized and fused through a generalized weighted limit state function, where failure is defined as gyroscope-level performance failure. Closed-form reliability expressions are derived for linear limit states, while Monte Carlo simulation is used for nonlinear cases. Reduced-order multiphysics simulation cases, including a double-ended fixed beam and a cantilevered MEMS mass block, are used to demonstrate the mechanism-to-indicator-to-reliability modeling procedure. The results show that the proposed dual-indicator framework provides more balanced reliability assessment than single-indicator analysis under the simulation setting. The proposed method offers an alternative mechanism-informed approach for reliability analysis and lifetime prediction of other MEMS devices.

Indexed as

MEMSmulti-mechanismreliability assessment

Identifiers

PMID42356747
PMCPMC13306981

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