TSViT: A Time Series Vision Transformer for Fault Diagnosis of Rotating Machinery

Efficient and accurate fault diagnosis of rotating machinery is extremely important. Fault diagnosis methods using vibration signals based on convolutional neural networks (CNNs) have become increasingly mature. They often struggle with capturing the temporal dynamics of vibration signals. To overco...

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Bibliografiske detaljer

Principais autores:	Shouhua Zhang, Jiehan Zhou, Xue Ma, Susanna Pirttikangas, Chunsheng Yang
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-11-01
Serier:	Applied Sciences
Fag:	vision transformer fault diagnosis rotating machinery deep learning
Online adgang:	https://www.mdpi.com/2076-3417/14/23/10781
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