Bearing fault diagnosis using lightweight and robust one-dimensional convolution neural network in the frequency domain
The massive environmental noise interference and insufficient effective sample degradation data of the intelligent fault diagnosis performance methods pose an extremely concerning issue. Realising the challenge of developing a facile and straightforward model that resolves these problems, this study...
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Main Authors: | , , , , , , |
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Format: | Article |
Published: |
MDPI
2022
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Subjects: | |
Online Access: | http://eprints.um.edu.my/41558/ |
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