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

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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Bibliographic Details
Main Authors: Kaixu Han, Wenhao Wang, Jun Guo
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Machines
Subjects:
convolutional neural network
long short-term memory network
gated recurrent unit (GRU)
fault diagnosis
rolling bearing
Online Access:https://www.mdpi.com/2075-1702/12/12/927
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