Dip3102001/Paderborn-diagnosis
A comprehensive repository for motor fault diagnosis experiments using the Paderborn Bearing Dataset. This project explores deep learning-based feature extraction, ensemble modeling (CNNs, Transformers), and data augmentation techniques to enhance fault classification. Includes automated pipelines for preprocessing, training, and evaluation.
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