2024
DOI: 10.1088/1361-6501/ad50fb
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Dynamic simulation-assisted Gaussian mixture alignment approach for fault diagnosis of rotation machinery under small samples

Shubo Yu,
Zhansheng Liu,
Gaorong Zhang
et al.

Abstract: Obtaining a substantial number of actual samples for rotating machinery in an industrial setting can be challenging, particularly when faulty samples are acquired under hazardous working conditions. The issue of insufficient samples hinders the effective training of reliable fault diagnosis models, impeding the industrial implementation of advanced intelligent methods. This study proposes an innovative Dynamic Simulation-assisted Gaussian Mixture Alignment model (DSGMA) to address the challenge of applying fau… Show more

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