Aadil Arshad Ferhath

Machine learning-based fault detection in low-speed bearings using a multi-environmental dataset

The near-perfect linear separability indicates that the dataset’s binary, controlled-laboratory labelling rather than intrinsic bearing-degradation physics drives the clean classification, and validation on 500–1000 or more samples with progressive-degradation labelling is essential before any operational claim can be supported.