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Xutao Lu, Xingpeng An, Minghuan He
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IEVAEGAN: An input enhancement VAEGAN for rotating component fault diagnosis with extremely limited data
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A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
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Global contextual residual convolutional neural networks for motor fault diagnosis under variable-speed conditions
10.1016/j.ress.2022.108618 · doi-reference
A novel local binary temporal convolutional neural network for bearing fault diagnosis
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10.1016/j.iref.2024.04.002 · doi-reference
Industrial intelligence-driven production and operations management
10.1080/00207543.2023.2207956 · doi-reference
Intelligent fault diagnosis technology for mechanical equipment: Current status and development
10.63313/sd.2002 · doi-reference
10.3390/app15031389
10.3390/app15031389 · doi-reference
A review on vibration monitoring techniques for predictive maintenance of rotating machinery
10.3390/eng4030102 · doi-reference