2024
DOI: 10.1049/elp2.12508
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A novel method based on the SCNGO‐ICEEMDAN and MCNN‐BiLSTM model for fault diagnosis of motor bearings for more electric aircraft

Dongsheng Yuan,
Feng Liu,
Zhonggang Yin
et al.

Abstract: The fault signal characteristics of motor rolling bearings for more electric aircraft are easily masked by strong background noise. Directly using machine learning, deep learning, or other methods results in a lower accuracy in fault recognition. In this article, a Northern Goshawk algorithm using a fusion subtraction optimiser and Cauchy strategy (SCNGO) is proposed to optimise the number of white noise additions and amplitude weights in the improved full set empirical mode decomposition method based on adapt… Show more

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