Evidence map›Paper›PMID 41900260›Full record

ArticleMicromachines2026

Fault Detection and Isolation of MEMS IMU Array Based on WOA-MVMD-GLT.

Hanyan Li, Fayou Sun, Jingbei Tian, Xiaoyang He, Ting Zhu

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.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Hanyan LiSchool of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.
Fayou SunSchool of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.
Jingbei TianSchool of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.
Xiaoyang HeSchool of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.
Ting ZhuSchool of Automation, Guangxi University of Science and Technology, Liuzhou 545006, China.ORCID 0000-0001-8633-4877

Funding

Doctoral Fund of Guangxi University of Science and Technology 22Z32Guangxi Natural Science Foundation 2025GXNSFHA069185National Natural Science Foundation of China 62363001
6 · The paper itself

Abstract

The stable and accurate output of the inertial measurement unit array (IMU) of a micro-electro-mechanical system (MEMS) is the key to ensuring the data fusion of the MEMS IMU array. However, due to the large number of MEMS IMUs contained in the MEMS IMU array, it is susceptible to interference and has difficulty avoiding failures. The output of the MEMS IMU contains noise, outliers, and other related errors, which can seriously lead to low fault detection and isolation accuracy in the MEMS IMU. In this study, a new method of fault detection and isolation based on multivariate variational mode decomposition (MVMD), a whale optimization algorithm (WOA), and a generalized likelihood test (GLT) is proposed, which is called WOA-MVMD-GLT. Firstly, a multi-index fitness function WOA is proposed to optimize the parameters of MVMD. Secondly, MVMD is used to extract the features of the MEMS IMU's signals. Finally, a GLT is used to construct a fault detection function and a fault isolation function to detect and isolate the faults of gyroscopes and accelerometers. The experimental results show that the method proposed in this paper can significantly reduce the false alarm rate and false isolation rate.

Indexed as

fault detection and isolationgeneralized likelihood testMEMS IMU arraymultivariate variational mode decompositionwhale optimization algorithm

Identifiers

PMID41900260
PMCPMC13029744

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