An Imbalanced Fault Diagnosis Method Based on TFFO and CNN for Rotating Machinery

An Imbalanced Fault Diagnosis Method Based on TFFO and CNN for Rotating Machinery

Deep learning-based fault diagnosis usually requires a rich supply of data, but fault samples are scarce in practice, posing a considerable challenge for existing diagnosis approaches to achieve highly accurate fault detection in real applications. This paper proposes an imbalanced fault diagnosis o...

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Bibliographic Details
Main Authors: Long Zhang, Yangyuan Liu, Jianmin Zhou, Muxu Luo, Shengxin Pu, Xiaotong Yang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
imbalanced data
data expansion
continuous wavelet transform
synthetic minority oversampling technique
convolution neural network
Online Access:https://www.mdpi.com/1424-8220/22/22/8749

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