Time-Frequency Multi-Domain 1D Convolutional Neural Network with Channel-Spatial Attention for Noise-Robust Bearing Fault Diagnosis

This paper proposes a noise-robust and accurate bearing fault diagnosis model based on time-frequency multi-domain 1D convolutional neural networks (CNNs) with attention modules. The proposed model, referred to as the TF-MDA model, is designed for an accurate bearing fault classification model based...

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Detaylı Bibliyografya
Asıl Yazarlar:	Yejin Kim, Young-Keun Kim
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2023-11-01
Seri Bilgileri:	Sensors
Konular:	multi-domain fusion bearing fault diagnosis PHM attention noise robustness fault classification
Online Erişim:	https://www.mdpi.com/1424-8220/23/23/9311
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Time-Frequency Multi-Domain 1D Convolutional Neural Network with Channel-Spatial Attention for Noise-Robust Bearing Fault Diagnosis

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