Towards a more realistic evaluation of machine learning models for bearing fault diagnosis
arXiv:2509.22267v4 Announce Type: replace Abstract: Reliable detection of bearing faults is essential for maintaining the safety and operational efficiency of rotating machinery. While recent advances