Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model

In view of the problem of the insufficient performance of deep learning models in time series prediction and poor comprehensive space–time feature extraction, this paper proposes a diagnostic method (CNN-LSTM-GRU) that integrates convolutional neural network (CNN), long short-term memory (LSTM) netw...

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Hlavní autoři:	Kaixu Han, Wenhao Wang, Jun Guo
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-12-01
Edice:	Machines
Témata:	convolutional neural network long short-term memory network gated recurrent unit (GRU) fault diagnosis rolling bearing
On-line přístup:	https://www.mdpi.com/2075-1702/12/12/927
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Research on a Bearing Fault Diagnosis Method Based on a CNN-LSTM-GRU Model

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