Rolling Bearing Fault Diagnosis Based on VMD-DWT and HADS-CNN-BiLSTM Hybrid Model

This study proposes a hybrid framework for rolling bearing fault diagnosis by integrating a Variational Mode Decomposition–Discrete Wavelet Transform (VMD-DWT) with a Hybrid Attention-Based Depthwise Separable CNN-BiLSTM (HADS-CNN-BiLSTM) to address noise interference and low diagnostic accuracy und...

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Detalles Bibliográficos

Principais autores:	Luchuan Shao, Bing Zhao, Xutao Kang
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-05-01
Series:	Machines
Assuntos:	signal reconstruction hybrid attention mechanism depthwise separable convolution bidirectional long short-term memory rolling bearings fault diagnosis
Acceso en liña:	https://www.mdpi.com/2075-1702/13/5/423
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