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March 3, 2026Mechanical Systems and Signal Processing1 citations

Adaptive filtering and multi-scale MixStyle network for cross-domain fault diagnosis of marine electric thruster bearings

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CSChenxing ShengMZMeng ZhangXRXiang Rao

Key Points

  • Improved fault diagnosis was observed with an advanced multi-scale MixStyle network, leading to enhanced accuracy.
  • The study demonstrated a reduction in classification errors by over 25% using adaptive filtering techniques.
  • Analysis employed a novel adaptive filtering approach across various marine environments and fault scenarios.
  • These findings underscore the potential for cross-domain applications in marine systems, though real-world validation is needed.
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Cite This Study

Sheng et al. (2026) studied this question.

synapsesocial.com/papers/69a75b90c6e9836116a2311ahttps://doi.org/10.1016/j.ymssp.2026.113910
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Task-Sequencing Meta Learning for Intelligent Few-Shot Fault Diagnosis With Limited Data2021 · 176 citations
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  5. 5Spare optimistic based on improved ADMM and the minimum entropy de-convolution for the early weak fault diagnosis of bearings in marine systems2017 · 47 citations