A. Sivathanu

Machine learning based predictive maintenance framework for belt-pulley systems

A machine-learning-based system for fault identification and classification based on vibration, slip ratio, and belt-tension measurements obtained from a controlled experimental setup demonstrates machine learning’s potential for scaled implementation in industrial predictive maintenance settings and establishes its applicability for belt-pulley systems’ real-time health evaluation.