The paper claims 98.1% accuracy on CWRU bearing fault classification with a Transformer that separates attention into trend and seasonal components, but the method and experiments are too poorly specified to support the claim.
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Transformer-Based Bearing Fault Detection using Temporal Decomposition Attention Mechanism
The paper claims 98.1% accuracy on CWRU bearing fault classification with a Transformer that separates attention into trend and seasonal components, but the method and experiments are too poorly specified to support the claim.