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September 20, 2025ElectronicsOpen Access

A Synergistic Fault Diagnosis Method for Rolling Bearings: Variational Mode Decomposition Coupled with Deep Learning

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A hybrid VMD-CNN-Transformer model improves fault diagnosis in rolling bearings, indicating significant advancements.

A fault diagnosis accuracy of 99.48% was achieved using the hybrid model on bearing signals.
The model effectively decomposes vibration signals into intrinsic mode functions for better analysis.
Utilizing CNN and Transformer, the method captures both local and global features of the signals.
This approach offers a new technical path for intelligent diagnosis of bearing faults.

Wang et al. (2025) studied this question.

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