A multi-channel CNN fault diagnosis method based on squeeze-and-convolution attention for rotating machinery

A multi-channel CNN fault diagnosis method based on squeeze-and-convolution attention for rotating machinery

Deep learning methods are increasingly being applied in fault diagnosis because of the capability of representing internal correlations through network structures and extracting hidden features from original data. Convolutional neural networks (CNNs) can perceive local features through convolutional...

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Bibliographic Details
Main Authors: Xu YANG, Jingyi ZHU, Jian HUANG
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2024-12-01
Series:Journal of Advanced Mechanical Design, Systems, and Manufacturing
Subjects:
convolutional neural networks (cnn)
attention mechanism
rotating machinery
fault diagnosis
rolling bearing
Online Access:https://www.jstage.jst.go.jp/article/jamdsm/18/8/18_2024jamdsm0097/_pdf/-char/en
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