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

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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Bibliographic Details
Main Authors: Shouhua Zhang, Jiehan Zhou, Xue Ma, Susanna Pirttikangas, Chunsheng Yang
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
vision transformer
fault diagnosis
rotating machinery
deep learning
Online Access:https://www.mdpi.com/2076-3417/14/23/10781
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