Fault Diagnosis of Rotating Machines Based on Combination of One-Dimensional Convolutional Neural Network and Long Short-Term Memory in Variable Working Conditions

Fault Diagnosis of Rotating Machines Based on Combination of One-Dimensional Convolutional Neural Network and Long Short-Term Memory in Variable Working Conditions

Deep learning models, particularly one-dimensional convolutional neural networks (1D CNNs), have shown great potential in the fault diagnosis of rotating machines. However, standard 1D CNNs face challenges in capturing long-term dependencies in time series data. To overcome this, various studies hav...

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Bibliographic Details
Main Authors:	Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen
Format:	Article
Language:	English
Published:	Wiley 2025-01-01
Series:	Journal of Engineering
Online Access:	http://dx.doi.org/10.1155/je/1670810
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