A New Method for Bearing Fault Diagnosis across Machines Based on Envelope Spectrum and Conditional Metric Learning

In recent years, most research on bearing fault diagnosis has assumed that the source domain and target domain data come from the same machine. The differences in equipment lead to a decrease in diagnostic accuracy. To address this issue, unsupervised domain adaptation techniques have been introduce...

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Autores principales:	Xu Yang, Junfeng Yang, Yupeng Jin, Zhongchao Liu
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-04-01
Colección:	Sensors
Materias:	fault diagnosis conditional metric learning envelope spectrum convolutional neural network
Acceso en línea:	https://www.mdpi.com/1424-8220/24/9/2674
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