An IoT-based System for Early Fault Detection and Predictive Maintenance in Induction Motors with Interpretable Generalized Additive Neural Networks
The proposed IoT-MDS-EDFIM-IGANN framework is efficient, accurate, and cost-effective solution for induction motor fault diagnosis and combines advanced preprocessing, class balancing, feature extraction, and optimization to achieve reliable predictive maintenance and promote operational reliability of industrial induction motor systems.