Adaptive Dynamic Threshold Graph Neural Network: A Novel Deep Learning Framework for Cross-Condition Bearing Fault Diagnosis

Adaptive Dynamic Threshold Graph Neural Network: A Novel Deep Learning Framework for Cross-Condition Bearing Fault Diagnosis

Recently, bearing fault diagnosis methods based on deep learning have achieved significant success. However, in practical engineering applications, the limited labeled data and various working conditions severely constrain the widespread application of most deep-learning-based fault diagnosis method...

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Xehetasun bibliografikoak
Egile Nagusiak: Linjie Zheng, Yonghua Jiang, Hongkui Jiang, Chao Tang, Weidong Jiao, Zhuoqi Shi, Attiq Ur Rehman
Formatua: Artikulua
Hizkuntza:English
Argitaratua: MDPI AG 2023-12-01
Saila:Machines
Gaiak:
deep learning
bearing fault diagnosis
graph neural network
few-shot learning
cross-condition
Sarrera elektronikoa:https://www.mdpi.com/2075-1702/12/1/18

Internet

https://www.mdpi.com/2075-1702/12/1/18

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